{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "960ceacb-3c3f-484c-95b9-172bd009b1a4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is a generic code for drawing a state's Home Districts for neutral map estimation\n",
      "In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\n"
     ]
    }
   ],
   "source": [
    "#  THIS IS THE PRIMARY VERSION TO USE FOR ALL STATES  #See MO for orig 2/10/24.  This one from MI 4-6-24\n",
    "print(\"This is a generic code for drawing a state's Home Districts for neutral map estimation\") #Jan'24\n",
    "print(\"In this code, we use the term 'tract' generically to refer the base building block, usually vtd's\")\n",
    "import shapely\n",
    "from shapely.geometry import Point, LineString, Polygon\n",
    "from shapely.ops import nearest_points, transform\n",
    "from shapely.affinity import translate, scale\n",
    "import geopandas as gpd\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import random\n",
    "from scipy.stats import norm\n",
    "from scipy.optimize import minimize, minimize_scalar\n",
    "import math\n",
    "import time\n",
    "import ast\n",
    "# from HDmethods import *   #I want to implement this, but my HDmethods require shapely functions\n",
    "# see https://stackoverflow.com/questions/66877728/proper-way-to-use-import-when-calling-external-function for a future workaround\n",
    "\n",
    "dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "#handy function for plotting Polygon or multiPolygon tracts and precincts\n",
    "def plotPoly(inputPoly,LW=1):\n",
    "    dummyPoly = Polygon([(0,0),(0,1),(1,1)])\n",
    "    if inputPoly.geom_type == dummyPoly.geom_type:\n",
    "        x,y = inputPoly.exterior.xy\n",
    "        plt.plot(x,y,lw=LW)\n",
    "    else:\n",
    "        for geom in inputPoly.geoms:\n",
    "            if geom.area > 0:  #to avoid error with LineString geom parts\n",
    "                x,y = geom.exterior.xy\n",
    "                plt.plot(x,y,lw=LW)  \n",
    "def plotCenter(t,geom,FONTSIZE=10):\n",
    "    plt.text(geom.centroid.x,geom.centroid.y,t,ha='center',fontsize=FONTSIZE)\n",
    "    \n",
    "def r3(number):\n",
    "    result = round(number,3)\n",
    "    return result\n",
    "\n",
    "def r5(number):\n",
    "    result = round(number,5)\n",
    "    return result\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "2ab4a3d5-f4e7-4aec-b81c-0e786cd35b57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "def getWeightedAvgAndSD(LIST, WEIGHTS):  #from IN\n",
    "    nWeights = len(WEIGHTS)\n",
    "    normWeights = [WEIGHTS[i] / np.sum(WEIGHTS) for i in range(nWeights) ]\n",
    "    AVG = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        AVG += normWeights[i] * value\n",
    "    sumVar = 0.\n",
    "    for i, value in enumerate(LIST):\n",
    "        sumVar += normWeights[i] * (value - AVG)**2\n",
    "    SD = sumVar ** 0.5     #don't need to normalize again since weights were normalized\n",
    "    return AVG, SD\n",
    "\n",
    "def squish(shapeList, cutLINE, farLINE, newFarLINE):\n",
    "    \"\"\"\n",
    "    This method compresses a list of shapes lying between the cutLINE and the farLINE)\n",
    "    such that the Polygons now lie between the cutLINE and the newFarLINE, which is closer to the cutLINE\n",
    "    Used to compress state outcroppings into a more compact state representation.\n",
    "     (I tried doing this point by point (see #'s), but this overdistorted geometries.)\n",
    "      (#This was a manual alternative to shapely.affinity.scale and .translate operations)\n",
    "       So instead, we run this AFTER established untransformed map topology, and \n",
    "        we simply scale and translate each unit.  This loses true connectivity.\n",
    "        Scaling is all lengths scale by compression of distance\n",
    "    The cut, far, and newFar LineString segments are preferably parallel\n",
    "    The method returns the modified shapes of all pollys\n",
    "    \"\"\"\n",
    "    if cutLINE.intersects(farLINE) or cutLINE.intersects(newFarLINE):\n",
    "        print(\"cutLine,farLine, newFarLine were\",cutLINE, farLINE, newFarLINE)\n",
    "        raise Exception(\"ERROR: the proposed cutLine intersects the current or proposed far line\")\n",
    "    newPollys = list()\n",
    "    for polly in shapeList:\n",
    "        pollyCP = polly.centroid\n",
    "        cutPt =     nearest_points(cutLINE,   pollyCP)[0]\n",
    "        farPt =     nearest_points(farLINE,   pollyCP)[0]\n",
    "        newFarPt =  nearest_points(newFarLINE,pollyCP)[0]\n",
    "        curr_cutX, curr_cutY =            pollyCP.x - cutPt.x, pollyCP.y -  cutPt.y\n",
    "        currFar_CutX , currFar_CutY  =    farPt.x - cutPt.x, farPt.y   -  cutPt.y\n",
    "        new_currFarX, new_currFarY =      newFarPt.x - farPt.x, newFarPt.y - farPt.y\n",
    "        newFar_CutX,  newFar_CutY =       newFarPt.x - cutPt.x, newFarPt.y   -  cutPt.y\n",
    "        distanceRatio = newFarPt.distance(cutPt)/farPt.distance(cutPt) #scale area ^length^2\n",
    "        XOFF,YOFF = 0., 0.\n",
    "        XFACT, YFACT = 1., 1.  #default = no stretch\n",
    "        # basic equation: (new-cut)/(curr-cut) = (newFar-cut)/(currFar - cut)\n",
    "        #  or: (new-curr)  = (curr-cut)*(newFar-currFar)/(currFar - cut)   # -1 to both sides\n",
    "        if currFar_CutX != 0:\n",
    "            XOFF =  curr_cutX * new_currFarX / currFar_CutX\n",
    "            XFACT =              newFar_CutX / currFar_CutX\n",
    "        if currFar_CutY != 0:\n",
    "            YOFF =  curr_cutY * new_currFarY / currFar_CutY\n",
    "            YFACT =              newFar_CutY / currFar_CutY\n",
    "        newPolly = translate(polly,xoff=XOFF,yoff=YOFF)\n",
    "        newPolly = scale(newPolly, xfact=XFACT, yfact=YFACT, origin='centroid')\n",
    "        newPollys.append( newPolly )       \n",
    "    return newPollys\n",
    "\n",
    "def getHDcp(TRACTCP,TRACTPOP, TRACTLIST, SPLITTRACTNO = -777,SPLITTRACTUSE = 1.):  #population centerpoint of a Home District or county (cluster)\n",
    "    cpx, cpy, sumPop = 0.,0., 0.\n",
    "    for tt in TRACTLIST:\n",
    "        USE = 1.\n",
    "        if tt ==    SPLITTRACTNO:\n",
    "            USE =   SPLITTRACTUSE\n",
    "        sumPop += USE*TRACTPOP[tt]\n",
    "        cpx +=    USE*TRACTPOP[tt] * TRACTCP[tt].x\n",
    "        cpy +=    USE*TRACTPOP[tt] * TRACTCP[tt].y\n",
    "    HDCP_ = Point(cpx/sumPop, cpy/sumPop)\n",
    "    return HDCP_\n",
    "\n",
    "#  The below four methods are TO SNAP to HD SHAPES without any solving / iteration\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    The optional xScale parameter is the ratio of longitude to latitude lengths scales (<<1 for far from equator)\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def buildPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a 4-tri polygon from four HD wedges emanating from the centerpoint\n",
    "    Pt = [Point(0,0)]*12                      #xScale has same meaning as in buildWedge\n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW]  #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ]  \n",
    "        Pt[nW*2] =   Point(CP.x + RADII[nW]/XSCALE*math.cos(ccwAngle), CP.y + RADII[nW]*math.sin(ccwAngle) )\n",
    "        Pt[nW*2+1] = Point(CP.x + RADII[nW]/XSCALE*math.cos( cwAngle), CP.y + RADII[nW]*math.sin( cwAngle) )        \n",
    "    POLLY = Polygon([Pt[0],Pt[1],Pt[2],Pt[3],Pt[4],Pt[5],Pt[6],Pt[7] ])\n",
    "    return POLLY\n",
    "\n",
    "def buildArcPoly(CP, RADII, ANGLES, XSCALE = 1.0):  #reconstructs a fuller polygon from four HD wedges emanating from the centerpoint\n",
    "    twoPi = 2. * 3.1415926   #xScale has same meaning as in buildWedge\n",
    "    POINTS = list()                   \n",
    "    for nW in range(4): \n",
    "        ccwAngle = ANGLES[nW] % twoPi                 #these two are the angles at start and end of nth wedge\n",
    "        cwAngle =  ANGLES[ int((nW+1)%4) ] % twoPi \n",
    "        midAngle = [0.75*ccwAngle + 0.25*cwAngle , 0.25*ccwAngle + 0.75*cwAngle ]  #avoid s sampling cone center for wide angles\n",
    "        if abs (ccwAngle - cwAngle) > 3.1415926 :  #angles straddle angle=0\n",
    "            midAngle = [0.75*(ccwAngle - twoPi) + 0.25*cwAngle , 0.25*(ccwAngle -twoPi) + 0.75*cwAngle ]\n",
    "        angList = [ccwAngle] + midAngle + [cwAngle]\n",
    "        for ang in angList:\n",
    "            POINTS.append(Point(CP.x + RADII[nW]/XSCALE*math.cos(ang), CP.y + RADII[nW]*math.sin(ang) ) )\n",
    "                          \n",
    "    POLLY = Polygon(POINTS)\n",
    "    return POLLY\n",
    "\n",
    "def getPolyPop(POLLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points contained by a polygon\n",
    "    WPOP, WLIST = 0., list()\n",
    "    for tt in CANDIDATELIST:\n",
    "        if POLLY.contains(TRACTCP[tt]):\n",
    "            WPOP += TRACTPOP[tt]\n",
    "            WLIST.append(tt)\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonCPP(POLLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county in getPolyPop\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if POLLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getNonHCunits(POLLY, HC, UNITLIST, UNITCP, UNITPOP, ALLFUSEDCOUNTIES, AREAFRAC, COUNTYGEOM, \n",
    "                  NEIGHBORCOUNTYLIST, COUNTYUNITLIST):\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a POLLY polygon for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county.  This should be more efficient than probing every unit in the map\n",
    "    After each county is checked, it goes into the checked list so we don't re-check, then we recursively probe county neighbors\n",
    "    \"unit counties\" are added as whole units if a sufficient area fraction is captured.  For non-unitCs, we probe each component vtd / tract\n",
    "    \"\"\"\n",
    "    UPOP, ULIST = 0., list()\n",
    "    checkedClist = [HC]   #dynamic list of counties we've already checked.  We probed the home county before we called this method\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        #1/9/24 - DO WE NEED TO MODIFY THE ORDER BELOW TO AVOID CREATING HOLES AND ENCLAVES ??  #\n",
    "        \n",
    "        for c in latestClist:\n",
    "            for cc in list( set(NEIGHBORCOUNTYLIST[c]).difference(set(ALLFUSEDCOUNTIES)) ):\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        if cc+0.5 in UNITLIST:\n",
    "                            if POLLY.intersection(COUNTYGEOM[cc]).area >=  AREAFRAC[cc] * COUNTYGEOM[cc].area :\n",
    "                                intersectedClist.append(cc)   #for unit counties, intersections count only if they capture sufficient area\n",
    "                                newClist.append(cc)\n",
    "                                UPOP += UNITPOP[UNITLIST.index(cc+0.5)]\n",
    "                                ULIST.append( UNITLIST.index(cc+0.5) )\n",
    "                        else:                           \n",
    "                            intersectedClist.append(cc)\n",
    "                            newClist.append(cc)\n",
    "                            if POLLY.contains(COUNTYGEOM[cc]):\n",
    "                                unitsToAdd = COUNTYUNITLIST[cc]\n",
    "                                UPOP += np.sum(  [ UNITPOP[uu] for uu in unitsToAdd ]  )\n",
    "                                ULIST += unitsToAdd\n",
    "                            else:\n",
    "                                for uu in COUNTYUNITLIST[cc]:\n",
    "                                    if POLLY.contains(UNITCP[uu]):\n",
    "                                        UPOP += UNITPOP[uu]\n",
    "                                        ULIST.append(uu)\n",
    "        latestClist = newClist.copy()\n",
    "        \n",
    "    return UPOP, ULIST\n",
    "\n",
    "def clusterSwell(CP_, CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, borderUnits, TGTPOP):\n",
    "    \"\"\"\n",
    "    This method grows a Home District by \"swelling\" from a corner county cluster.  First, we add the full cluster,\n",
    "     then we add closest neighbor units to the home district centerpoint CP_ until we reach the TGTPOP\n",
    "     new for MN 4/7/24 - don't enforce contiguity here -- too slow -- fix in cleanup stage instead\n",
    "     \"\"\"\n",
    "    hd_CCBdist = [CP_.distance(geo) for geo in CCBgeom]\n",
    "    CCBno = hd_CCBdist.index(np.min(hd_CCBdist))  #ID's the closest cluster to this HD center.  Should contain the HD, but rarely will not\n",
    "    unitNo = allUnits.index(CCBno+0.25)\n",
    "    newList, prevList, addedList, addedPop = [unitNo], [unitNo], [unitNo], unitPop[unitNo]  #seed with the cluster pop and unit\n",
    "    while addedPop < 0.99 * TGTPOP and len(newList) > 0:\n",
    "        tryList = getAdjoiners(addedList,unitNbrs)\n",
    "        tryDist = [ CP_.distance(unitCP[UU]) for UU in tryList ]\n",
    "        idx = np.argsort(tryDist)\n",
    "        idxNo, newList = 0, list()\n",
    "        haveNotAdded = True\n",
    "        while idxNo < len(tryList) and haveNotAdded:\n",
    "            UU = tryList[idx[idxNo]]\n",
    "            if unitPop[UU] + addedPop < 1.01 * TGTPOP :  #and wontEnclave(UU, addedList, unitNbrs, borderUnits) :  #we'll post-fix contig'y\n",
    "                newList.append(UU)\n",
    "                addedList.append(UU)\n",
    "                addedPop += unitPop[UU]\n",
    "                haveNotAdded = False\n",
    "            idxNo +=1\n",
    "        prevList = newList.copy()\n",
    "        \n",
    "    return addedPop, addedList\n",
    "            \n",
    "def getFakeHC(HDPOLLY, HC, CCBlist, countyGeom, MAP) :\n",
    "    \"\"\"\n",
    "    This method is for setting a fake home county for counties in corner clusters, so that county neighbors can be found budding from the \"home county\"\n",
    "    We pick the county in the cluster closest to the map center and intersecting the HDpoly.  This will be an active county on the cluster boundary   \n",
    "    \"\"\"\n",
    "    MAPcenter = MAP.centroid\n",
    "    for L in CCBlist:\n",
    "        if HC in L:\n",
    "            distList, cList = list(), list()\n",
    "            for C in L:\n",
    "                if HDPOLLY.intersects(countyGeom[C]):\n",
    "                    distList.append(countyGeom[C].distance(MAPcenter))\n",
    "                    cList.append(C)\n",
    "    fakeHC = cList[distList.index(np.min(distList)) ]\n",
    "    return fakeHC\n",
    "\n",
    "def getLongDist(CP1, CP2, xScale = 1.0): #distance between two points with EW distance scaled down by latitude\n",
    "    #LAT = MAP.centroid.y\n",
    "    #xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "    dist = ( xScale*xScale * (CP1.x - CP2.x)*(CP1.x - CP2.x)  +  (CP1.y - CP2.y)*(CP1.y - CP2.y) ) **0.5 \n",
    "    return dist\n",
    "\n",
    "# THESE ARE THE METHODS USED IN SOLVING HD SHAPES\n",
    "def buildWedge(CP,STARTANGLE, ENDANGLE, RR,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    This method creates triangular wedges from a centerpoint, wedge start and end angles, and wedge radius.\n",
    "    It passes back a SINGLE wedge polygon\n",
    "    \"\"\"\n",
    "    A0 = STARTANGLE\n",
    "    A1 = ENDANGLE\n",
    "    PT1 = Point(CP.x + RR/XSCALE*math.cos(A0),  CP.y + RR*math.sin(A0) )\n",
    "    PT2 = Point(CP.x + RR/XSCALE*math.cos(A1),  CP.y + RR*math.sin(A1) )\n",
    "    WEDGEPOLY = Polygon( [CP,PT1, PT2 ])\n",
    "    return WEDGEPOLY\n",
    "\n",
    "def getCountyWP(T, WEDGEPOLY, TRACTCP, TRACTPOP, CANDIDATELIST ):  #simple capture of pop points in a wedge excluding a point\n",
    "        WPOP, WLIST = 0., list()\n",
    "        for tt in CANDIDATELIST:\n",
    "            if tt != T and WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                WPOP += TRACTPOP[tt]\n",
    "                WLIST.append(tt)\n",
    "        return WPOP, WLIST\n",
    "\n",
    "def getNonCWP(WEDGEPOLY, HC, TRACTCP, TRACTPOP, COUNTYGEOM, COUNTYPOP, COUNTYTRACTLIST, NEIGHBORCOUNTYLIST) : #nonCounty wedgePop\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by an infinite polygonal wedge for counties contiguous with the Home County (no hop-overs)\n",
    "    , EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def isIncludedA(STARTa, ENDa, TESTa): #determines if a test angle is between a start and end angle (True)\n",
    "    \"\"\"\n",
    "    The start angle must be less than the end angle when placed on the [0, 2 pi] interval  (ccw convention)\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    STARTa, ENDa, TESTa = STARTa % (2.*pi), ENDa % (2.*pi), TESTa % (2.*pi)  #place on the 2pi interval\n",
    "    isIncludedA = False\n",
    "    if STARTa  > ENDa :  #included angle straddles east\n",
    "        if   TESTa  >= STARTa or TESTa < ENDa :  #near-east between the two\n",
    "            isIncludedA = True\n",
    "    else:\n",
    "        if TESTa >= STARTa and TESTa < ENDa :  #normal case\n",
    "            isIncludedA = True\n",
    "    return isIncludedA\n",
    "\n",
    "def getNonCWP_c(STARTANGL, ENDANGL, HC, TRACTCP,TRACTPOP,COUNTYGEOM,COUNTYPOP,COUNTYTRACTLIST,\n",
    "                                    NEIGHBORCOUNTYLIST, UUDIST, UUANGLE, WEDGEPOLY) :\n",
    "    \"\"\"\n",
    "    This method computes the total pop captured by a polygonal wedge for counties contiguous with the Home County (no hop-overs),\n",
    "    EXCLUDING the home county for the centerpoint of the wedge.  This should be more efficient than going tract-by-tract\n",
    "    After each county is checked, it goes into the checked list so we don't re-check.  Next round = nonchecked neighbors of current round\n",
    "    Unlike its getNonCWP vanilla parent, this one uses angles rather than infinite wedges for units (still wedges for counties)\n",
    "    \"\"\"\n",
    "    WPOP, WLIST = 0., list()\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if WEDGEPOLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "                        if WEDGEPOLY.contains(COUNTYGEOM[cc]):\n",
    "                            WPOP += COUNTYPOP[cc]\n",
    "                            WLIST += COUNTYTRACTLIST[cc]\n",
    "                        else:\n",
    "                            for tt in COUNTYTRACTLIST[cc]:\n",
    "                                if isIncludedA(STARTANGL, ENDANGL, UUANGLE[tt]): #WEDGEPOLY.contains(TRACTCP[tt]):\n",
    "                                    WPOP += TRACTPOP[tt]\n",
    "                                    WLIST.append(tt)\n",
    "        #below is temp debug\n",
    "        #print(len(intersectedClist),WPOP, len(WLIST),\"counties probed, pop, len(tractList)\")\n",
    "        latestClist = newClist.copy()\n",
    "    return WPOP, WLIST\n",
    "\n",
    "def getExitAngle(CP,WEDGEPOLY, MAP, A0, A1):\n",
    "    \"\"\"\n",
    "    This code determines the orientation angle from a CenterPoint to the intersection of a wedge with an exterior boundary\n",
    "    If an intersection is not found, we just take the average angle of the wedge start/stop angles A0, A1 as this orientation angle\n",
    "    MAP must be a single polygon for this to work in the revised code (tho could run thru all polygons in MAP if a multipolygon)\n",
    "    \"\"\"\n",
    "    EXITANGLE = 0.5* (A0 + A1) #this will be the angle from the x-axis to the exit beeline\n",
    "    if WEDGEPOLY.intersects(MAP.exterior):\n",
    "        edgeLine = WEDGEPOLY.intersection(MAP.exterior) #true state boundary line where wedge crossed it\n",
    "        closePoint = nearest_points(edgeLine,CP)[0]\n",
    "        dx = closePoint.x - CP.x       #this and below lines were indented in original code***\n",
    "        dy = closePoint.y - CP.y\n",
    "        EXITANGLE =  pi/2. * np.sign(dy)  #default in case dx=0\n",
    "        if (dx != 0. ):\n",
    "            EXITANGLE = math.atan(dy/dx) + random.uniform(-0.01,0.01) #add wiggle to avoid exact NESW orientation in gridded states\n",
    "            if dx < 0. :  #use complementary atan solution; boundary is west of tract centroid\n",
    "                EXITANGLE = pi + EXITANGLE\n",
    "    return EXITANGLE # this reorients 0th wedge to face boundary's closest point\n",
    "\n",
    "def getNewAngles(mWP, tWP, ADP, LEVEL_L, MINADJRATIO, MAXANGLE, MAXANGLERATIO, nUNFILLEDWEDGES): \n",
    "    \"\"\"\n",
    "    This method classifies Home Districts based on how their post-reoriented equi-angle max wedge pops stack up vs targets,\n",
    "     then changes wedge angles in some situations to pick up more population along the boundary\n",
    "    If there is one wedge that will fall short of a quarter district pop, then we adjust angles if it is sufficiently short    \n",
    "    (Using \"HD2\" code, the opposite wedge's pop will be constrained as well.)\n",
    "    If there are two opposite-facing constrained wedges, we do not adjust angles\n",
    "    If there are two adjacent constrained wedges, we classify as a corner (no angle change) if the adjacent wedge is sufficiently constrained,\n",
    "      otherwise we treat as a single constrained wedge\n",
    "    If there are three constrained wedges, the angles are unchanged; we use the 4th wedge to pick up all pop\n",
    "    If all four wedges are constrained, there is an error and we raise a flag.\n",
    "    mWP is the quadlist of maxWedgePops we would get by extending each wedge to the MAP boundary\n",
    "    tWP is the quadlist of targetWedgePops\n",
    "    LEVEL_L is the non-dimensional distance to the boundary at which we no longer adjust wedge angles to drive more near-boundary pop\n",
    "    MAXANGLERATIO is the max ratio of the wide angle (facing the boundary) to the normal angle (e.g. 90deg for four wedges) ...\n",
    "    but this is truncated near-boundary to MAXANGLE (e.g. 1.8 pi/2 instead of increasing all the way to 1.9 pi/2)\n",
    "      NOTE THAT this code does not consider nearly-shorted wedges -- those are a separate method called later if all mWP's > tWP's\n",
    "    \"\"\"   \n",
    "    isChange = False   #default; we are NOT changing angles\n",
    "    printDebuggg = False\n",
    "    NWEDGES = len(mWP)\n",
    "    avgWedgeAngle = 2.*math.pi / NWEDGES\n",
    "    minW = mWP.index(np.min(mWP))  #index of the wedge with the lowest max wedge pop\n",
    "    oppW = int( int(minW + NWEDGES/2) % NWEDGES )  #and its opposing wedge\n",
    "    Lstar = ( mWP[minW] / (0.25*ADP) )**0.5  #shortest wedge's nondim'l distance to boundary\n",
    "    \n",
    "    case = \"keep same wedge angles\" #default; no unfillable wedges or all but one are unfillable\n",
    "    if nUNFILLEDWEDGES >= NWEDGES:\n",
    "        raise Exception(\"ERROR! ALL WEDGES ARE CONSTRAINED for tract\",t,\".  IMPOSSIBLE!!\")\n",
    "    if nUNFILLEDWEDGES == 1:\n",
    "        case = \"constrain opp wedge\"\n",
    "        if Lstar >= levelL :\n",
    "            case = \"keep same wedge angles\"  #not close enough to boundary to distort HD shape\n",
    "    if nUNFILLEDWEDGES == 0 or nUNFILLEDWEDGES == NWEDGES - 1:  #far from boundary or with only one wedge w/large pop\n",
    "        case = \"keep same wedge angles\"   \n",
    "    if nUNFILLEDWEDGES == 2:  #must determine if opposite or adjacent           \n",
    "        if mWP[oppW] < tWP[oppW]:  #shorted wedges oppose each other, so ...\n",
    "            case = \"keep same wedge angles\" #...the HD shape will naturally widen to pick up adjacent pop\n",
    "        else:  #we have 2 adjacent (non-opposing) shorted wedges... but how shorted?  ID the adjacent wedge\n",
    "            for nW in range(NWEDGES):\n",
    "                if mWP[nW] < tWP[nW] and nW != minW :\n",
    "                    adjW = nW  #this is the adjacent wedge\n",
    "                    adjRatio = mWP[adjW] / tWP[adjW]\n",
    "            if adjRatio < minAdjRatio:  #we're close to a corner (this adjacentWedge is significantly constrained)\n",
    "                case = \"keep same wedge angles\"\n",
    "                if printDebuggg :\n",
    "                    print(\"Not adjusting wedge angles for tract\",t,\"as 2nd-sparsest wedge\",adjW,\"has pop\",mWP[adjW] )\n",
    "            else:\n",
    "                case = \"constrain opp wedge\"  #we will set the angles and target pops as if the adj wedge were not constrained\n",
    "    \n",
    "    if case == \"keep same wedge angles\":\n",
    "        isChange = False\n",
    "        WEDGEANGLE = [avgWedgeAngle for w in range(NWEDGES) ]\n",
    "\n",
    "    if case == \"constrain opp wedge\":  #Here, we modify wedge angles.  MWP's will be recalc'd outside the method\n",
    "        isChange = True  \n",
    "        wideAngle = min(MAXANGLE, avgWedgeAngle*max(  1,( 1.+(MAXANGLERATIO-1.)*(LEVEL_L - Lstar)/(LEVEL_L - 0.) )  ) )\n",
    "        WEDGEANGLE = [(2.*pi - 2. * wideAngle)/ (NWEDGES - 2.) for w in range(NWEDGES) ]  \n",
    "        WEDGEANGLE[minW] = wideAngle\n",
    "        WEDGEANGLE[oppW] = wideAngle\n",
    "    \n",
    "    return isChange, WEDGEANGLE\n",
    "\n",
    "def rebalanceTWPs(MWP, TWP, BARREDLIST=list()):\n",
    "    \"\"\"\n",
    "    This method iteratively increases targetWedgePops to accommodate wedges that have maxWedgePop < targetWedgePop.\n",
    "    The wedgePop gap is distributed equally among wedges that have some capacity and are not BARRED (e.g. an opposite wedge in HD2 method)\n",
    "     (If this pushes some wedges over capacity, this will be fixed in a later run through loop inside this method)\n",
    "    We also flag which wedges \"will fill\" = have sufficient capacity after the rebalancing of the targets to not use the entire maxWedgePoly\n",
    "    \"\"\"\n",
    "    DEBUGrTWP = False\n",
    "    NWEDGES = len(MWP)\n",
    "    unorderedCapacity = [MWP[w] - TWP[w] for w in range(NWEDGES) ]\n",
    "    idx = np.argsort(unorderedCapacity)\n",
    "    #for nn in range(NWEDGES):\n",
    "    #    print(MWP[idx[nn]])\n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        for nn in range(NWEDGES):\n",
    "            print(\"barred list, orig MWP, TWP\",BARREDLIST, r3(MWP[nn]),r3(TWP[nn]) )\n",
    "    \n",
    "    for nn in range(NWEDGES):  #going from least to most maxWedgePop here ...\n",
    "        nW = idx[nn]\n",
    "        if MWP[nW] < TWP[nW]: #need to redistribute extra target to higher-capacity wedges ...\n",
    "            wedgePopGap = TWP[nW] - MWP[nW]\n",
    "            TWP[nW] = MWP[nW]  #max out this wedge\n",
    "            nReceivers = 0.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....\n",
    "                    nReceivers += 1.\n",
    "            for WW in range(NWEDGES):\n",
    "                if MWP[WW] > TWP[WW] and WW not in BARREDLIST:  #this wedge could take at least a little more ....                    \n",
    "                    TWP[WW] += wedgePopGap / nReceivers  #... so give it equal share of the gap, even if this goes over; we'll correct in later loop\n",
    "                    \n",
    "    WILLFILL = [1]*NWEDGES\n",
    "    for nW in range(NWEDGES):\n",
    "        if MWP[nW] < 1.001* TWP[nW]:  #required pop nearly or truly requires the entire wedge\n",
    "            WILLFILL[nW] = 0 \n",
    "    if np.min(TWP) < 0.99 * np.average(TWP) and DEBUGrTWP:  #debug\n",
    "        print(\"adjusted TWP's are\",TWP)\n",
    "    return TWP, WILLFILL\n",
    "\n",
    "def solveWedge(nontractTWP,t, hC, STARTANGLE, ENDANGLE, MAXD, TOLERPOPS, tractCP, tractPop,\n",
    "               countyTractList, countyGeom, countyPop, neighborCountyLIST,XSCALE=1.0):\n",
    "    \"\"\"\n",
    "    #### NO LONGER USED; SEE FASTER SOLVEWEDGEB BASED ON UNIT-UNIT DISTANCES  *********\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop (which excludes the home tractPop)\n",
    "    The wedge has a fixed starting and ending angle.  Its maximum diameter is angle-related to max diameter of the state map\n",
    "    It uses bisection, NOT scipy minimize to minimize the square error in the wedge pop vs. target\n",
    "    The method passes back the final wedge pop and list of tracts in the wedge\n",
    "    \"\"\"\n",
    "    chgLoopNo, maxLoopNo = 10., 22.  #when we will start relaxing the pop tolerance, and when we give up\n",
    "    includedAngl = ENDANGLE - STARTANGLE\n",
    "    guessedR = MAXD / math.cos(0.5*includedAngl)  #max possible wedge radius, accounting for possible wide angle\n",
    "    popTol = TOLERPOPS[0]  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    #                      We loosen toward half the MAX tractPop if not converging\n",
    "    \n",
    "    offsetPop = 88888888.  #to force a reduction the first time through the loop\n",
    "    dr = guessedR\n",
    "    loopNo = 0\n",
    "    while abs(offsetPop) > popTol and loopNo < maxLoopNo:\n",
    "        loopNo +=1\n",
    "        popTol = max(TOLERPOPS[0], TOLERPOPS[0] + (TOLERPOPS[1] - TOLERPOPS[0]) * (loopNo - chgLoopNo) / (maxLoopNo - chgLoopNo) )\n",
    "        dr = 0.5*dr\n",
    "        guessedR -= dr*np.sign(offsetPop)\n",
    "        \n",
    "        guessedPoly = buildWedge(tractCP[t],STARTANGLE, ENDANGLE, guessedR,XSCALE) \n",
    "        iCP, iClist =  getCountyWP(t,guessedPoly, tractCP, tractPop, countyTractList[hC])\n",
    "        nonCP, nonClist = getNonCWP(guessedPoly, hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyLIST)\n",
    "        offsetPop = iCP + nonCP - nontractTWP\n",
    "        #print(t,loopNo,r5(guessedR),int(iCP),int(nonCP),r3(offsetPop+nontractTWP),r3(nontractTWP),\"t,loop,R,iCP,nonCP,pop,target\")\n",
    "        if loopNo >= maxLoopNo-1:\n",
    "            print(\"WARNING. Looped\",loopNo,\"times for t,angles,R\",t,r3(STARTANGLE),r3(ENDANGLE),r5(guessedR),\n",
    "                  \"wedgePop offset, target are\",int(offsetPop), int(nontractTWP) )    \n",
    "    finalPop = iCP + nonCP\n",
    "    finalList = iClist + nonClist\n",
    "    return finalPop, finalList, guessedR, loopNo\n",
    "\n",
    "#above = bisection.  Below solveWedgeB uses static unit-unit distances\n",
    "# Also tried scipy minimize, which doesn't seem any faster\n",
    "\n",
    "def solveWedgeB(nontractTWP,T, HC, POLLY, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that intersect,\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2x2 array\n",
    "    \"\"\"\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    \n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList = 0, 0, list()\n",
    "    notFull = True\n",
    "    while notFull :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist    \n",
    "\n",
    "def solveWedgeC(nontractTWP,T, HC, POLLY, STARTANGL, ENDANGL, TOLERPOP, TRACTCP, TRACTPOP, COUNTYNO,\n",
    "               COUNTYTRACTLIST, COUNTYGEOM, NEIGHBORCOUNTYLIST, UUDIST, UUANGLE):\n",
    "    \"\"\"\n",
    "    This heart of the code solves the wedge radius that gives the closest wedgePop to the TargetWedgePop\n",
    "    We first determine which counties intersect the maxWedgePop to reduce the candidate list\n",
    "    We then go through the tract list from closest to farthest, adding any (from candidate counties) that\n",
    "    fall within the angle range (in lieu of wedgeB's check for intersection),\n",
    "     until the target pop is reached. Note that the passed UUDIST is the slice for unit t, not the full 2D array\n",
    "    \"\"\"\n",
    "    pi = 3.141592653\n",
    "    popTol = TOLERPOP  #default tolerance = e.g. within 0.7 an AVERAGE tract's population.\n",
    "    STARTANGL, ENDANGL = STARTANGL % (2.*pi), ENDANGL % (2.*pi)\n",
    "    #preliminary - restrict the found units to those in contiguous counties to the home county\n",
    "    checkedClist = [HC]\n",
    "    intersectedClist = [HC]\n",
    "    latestClist = [HC]\n",
    "    while len(latestClist) > 0:\n",
    "        newClist = list()    #we loop until we don't find any more neighbors with intersection\n",
    "        for c in latestClist:\n",
    "            for cc in NEIGHBORCOUNTYLIST[c]:\n",
    "                if cc not in checkedClist:\n",
    "                    checkedClist.append(cc)\n",
    "                    if POLLY.intersects(COUNTYGEOM[cc]):\n",
    "                        intersectedClist.append(cc)\n",
    "                        newClist.append(cc)\n",
    "        latestClist = newClist.copy()\n",
    "    \n",
    "    idx = np.argsort(UUDIST)  #sort order from closest to farthest to the home unit\n",
    "    \n",
    "    i, capturedPop, capturedList, latestDist = 0, 0, list(), 0.00001  #dummy value\n",
    "    notFull = True\n",
    "    while notFull and i < len(UUDIST) - 2 :  #capturedPop < nontractTWP - popTol : \n",
    "        i +=1    #this skips over the home tract\n",
    "        TT = idx[i]\n",
    "        if COUNTYNO[TT] in intersectedClist and TT != T:  #just to be sure\n",
    "            if isIncludedA(STARTANGL, ENDANGL, UUANGLE[TT]) : #POLLY.contains(TRACTCP[TT]):\n",
    "                capturedPop += TRACTPOP[TT]\n",
    "                capturedList.append(TT)\n",
    "                latestDist = UUDIST[TT]\n",
    "            if capturedPop > nontractTWP - popTol:\n",
    "                notFull = False\n",
    "                \n",
    "    return capturedPop, capturedList, latestDist \n",
    "\n",
    "\n",
    "def getPartialTract(t, HDTRACTLIST, offsetPop, UUDIST, tractPop, neighborLIST):\n",
    "    \"\"\"\n",
    "    If offsetPop is >0, this method identifies the tract with centroid farthest from Home t that can jettison at least offsetPop ...\n",
    "    ... by slicing out part of this tract.\n",
    "    If offsetPop <0, we ID a tract CLOSEST to Home t among neighbors of in-HD tracts to pick up a partial\n",
    "    We return the tractID and its new partial use\n",
    "    We have updated this method to pass the uuDist slice for tract t instead of computing tract distances inside here\n",
    "    \"\"\"\n",
    "    debugGPT = False\n",
    "    NTRACTS = len(tractCP)\n",
    "    bigDist = 9999999.\n",
    "    qualifyingTractList = list()\n",
    "    isWholeTract = False\n",
    "    if offsetPop > 0:\n",
    "        homeDist = [0.]*NTRACTS  #default = 0 to not get picked\n",
    "        for TT in HDTRACTLIST:\n",
    "            if tractPop[TT] > offsetPop:\n",
    "                qualifyingTractList.append(TT)\n",
    "        for TT in qualifyingTractList:\n",
    "            homeDist[TT] = UUDIST[TT]\n",
    "        if len(qualifyingTractList) == 0:  #very rare case where all in-HD tracts are too small.  Jettison nearly the whole farthest one\n",
    "            isWholeTract = True\n",
    "            for TT in HDTRACTLIST:\n",
    "                if tractPop[TT] > 0.9*np.average(tractPop): #set arbitrary min qualifying pop\n",
    "                    homeDist[TT] = UUDIST[TT]\n",
    "        targetT = homeDist.index(np.max(homeDist))\n",
    "        partialUseFrac = max(0.0001,(tractPop[targetT] - offsetPop)/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(\"positive offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    else: #pick up a partial\n",
    "        homeDist = [bigDist]*NTRACTS\n",
    "        for TT in HDTRACTLIST:\n",
    "            for TTT in neighborList[TT]:\n",
    "                if TTT not in qualifyingTractList and TTT not in HDTRACTLIST and tractPop[TTT] > abs(offsetPop):\n",
    "                    qualifyingTractList.append(TTT)\n",
    "        for TTT in qualifyingTractList:\n",
    "            homeDist[TTT] = UUDIST[TTT]\n",
    "        if len(qualifyingTractList) == 0 :  #rare case where most nearby tracts are small.  Add nearly the whole biggest one\n",
    "            isWholeTract = True\n",
    "            maxPop = 0.\n",
    "            targetT = -999\n",
    "            for TT in HDTRACTLIST:\n",
    "                for TTT in neighborList[TT]:\n",
    "                    if TTT not in qualifyingTractList and TTT not in HDTRACTLIST : # we'll take just one, even if doesn't fill gap\n",
    "                        qualifyingTractList.append(TTT)\n",
    "            for TTT in qualifyingTractList:\n",
    "                if tractPop[TTT] > maxPop:\n",
    "                    targetT = TTT\n",
    "                    maxPop = tractPop[targetT]\n",
    "        else:\n",
    "            targetT = homeDist.index(np.min(homeDist))\n",
    "        partialUseFrac = min(0.9999, -1.* offsetPop/tractPop[targetT] )\n",
    "        if debugGPT:\n",
    "            print(t,\"'s negative offsetPop =\",offsetPop,\", ID'd tract\",targetT,\"with pop\",tractPop[targetT] )\n",
    "    \n",
    "    return targetT, partialUseFrac\n",
    "\n",
    "def getAdjoiners(UNITLIST, UNITNBRS): #returns all units that neighbor a UNITLIST but are not in the UNITLIST \n",
    "    allNbrs = list()\n",
    "    for U in UNITLIST:\n",
    "        allNbrs = allNbrs + UNITNBRS[U]\n",
    "    adjoiners = list( set(allNbrs).difference(set(UNITLIST)) )\n",
    "    return adjoiners\n",
    "\n",
    "def get2nbrs(ULIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    Get the combined list of first- and second-level neighbors of a LIST, using neighborList connectivity.  Excludes the source list\n",
    "    \"\"\"\n",
    "    firstList =  getAdjoiners(ULIST, UNITNBRS)\n",
    "    secondList = getAdjoiners(firstList, UNITNBRS)\n",
    "    twoLevelList = list( set(firstList + secondList).difference(set(ULIST) ) )\n",
    "    return twoLevelList\n",
    "\n",
    "def getContigFromStarter(starter, VLIST, NEIGHBORLIST):  #all contiguous units in VLIST, starting from starter unit\n",
    "    foundList, newList, prevList = [ starter ], [ starter ], [ starter ]\n",
    "    while len(newList) > 0:\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()        \n",
    "    return foundList   \n",
    "\n",
    "def isContiguous(VLIST,NEIGHBORLIST,returnBiggestPiece=False):\n",
    "    \"\"\"\n",
    "    This method determines if all items in a list form a continuous chain of neighbors based on the passed neighborlist\n",
    "    Empty lists are considered contiguous.  If discontiguous, a less-than-majority piece list is returned,\n",
    "     unless giveBig=True, in which case we return the biggest piece\n",
    "    \"\"\"    \n",
    "    isUnbroken, newList, foundList = True, list(), list()\n",
    "    if len(VLIST) > 0:\n",
    "        foundList, newList, prevList = [ VLIST[0] ], [ VLIST[0] ], [ VLIST[0] ]\n",
    "    while len(newList) > 0:  #this round's list of neighbors\n",
    "        newList = list()\n",
    "        for V in prevList:\n",
    "            for VV in NEIGHBORLIST[V]:\n",
    "                if VV in VLIST and VV not in foundList:\n",
    "                    newList.append(VV)\n",
    "                    foundList.append(VV)\n",
    "        prevList = newList.copy()      \n",
    "    pickedPieceList = foundList.copy()  #default contiguous sublist to pass back to main\n",
    "    \n",
    "    if len(foundList) < len(VLIST):  #not contiguous\n",
    "        isUnbroken  = False\n",
    "        pieceLists, remainingList = [foundList], list( set(VLIST).difference(set(foundList) ) )\n",
    "        if returnBiggestPiece == True:  #we were asked for the biggest piece, not a random small one, so we must find them all\n",
    "            if len(foundList) < 0.5*len(VLIST):\n",
    "                while len(remainingList) > 0:\n",
    "                    newList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                    pieceLists.append(newList)\n",
    "                    remainingList = list(set(remainingList).difference(set(newList)))\n",
    "                pieceLengths = [len(pL) for pL in pieceLists]\n",
    "                pickedPieceList = pieceLists[ pieceLengths.index(np.max(pieceLengths)) ]\n",
    "            \n",
    "        else: #quickly return a contiguous sub-list that's at most half the total units in the list\n",
    "            if len(foundList) > 0.5*len(VLIST): #pick a different piece; this one is the majority\n",
    "                pickedPieceList = getContigFromStarter(remainingList[0], remainingList, NEIGHBORLIST)\n",
    "                \n",
    "    return isUnbroken, pickedPieceList\n",
    "\n",
    "def enclaveCheck(UNITLIST,UNITNBRS,maxLoops=4):\n",
    "    \"\"\"\n",
    "    This method determines if a list of units has an unbroken boundary AND whether its complement has an unbroken boundary\n",
    "    If the complement boundary is broken, there is an enclave or the district is so disconnected its adjoining units aren't contiguous\n",
    "    The method returns contiguity of boundary and of its adjoiners.  Also returns the lists of boundary and complement-boundary units\n",
    "      If either of these is broken, only a contiguous sublist is returned that is guaranteed to be smaller than half (for finding enclaves)\n",
    "      maxLoops is the number of loops for expanding neighbors-of-neighbors for contiguity of the units outside the passed unit-list\n",
    "    \"\"\"\n",
    "    UNITSET = set(UNITLIST)\n",
    "    ADJLIST =  get2nbrs(UNITLIST, UNITNBRS)  #in case direct adjoiners are only queen-adjacent\n",
    "    #adjoinersOfAdjoiners = getAdjoiners(ADJLIST,  UNITNBRS)\n",
    "    #BDRYLIST = list( set(UNITLIST).intersection(set(adjoinersOfAdjoiners)) )  #this might fail for queen-adjacent boundary units\n",
    "    BDRYLIST = list (set(get2nbrs(ADJLIST,UNITNBRS)).intersection(UNITSET) )  #in case inHD boundary is only queen-adjacent\n",
    "    noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)  \n",
    "    unbroken, smallPieceList = isContiguous(BDRYLIST, UNITNBRS)\n",
    "    if not unbroken: #could be that district's boundary intersects the state boundary or there is a nonHD enclave inside the HD\n",
    "        unbroken, smallPieceList = isContiguous(UNITLIST, UNITNBRS)  #slower check for full district, not just its boundary \n",
    "    nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "    while nLoops <= maxLoops and not noEnclave:\n",
    "        nLoops +=1\n",
    "        newSet = set(ADJLIST)\n",
    "        for UU in ADJLIST:\n",
    "            newSet = newSet.union( set(UNITNBRS[UU]).difference(UNITSET) )\n",
    "        ADJLIST = list(newSet)\n",
    "        noEnclave, enclaveList =   isContiguous(ADJLIST, UNITNBRS)\n",
    "    #isJiggy = noEnclave and unbroken\n",
    "    return unbroken, noEnclave, smallPieceList, enclaveList\n",
    "\n",
    "def getBdryNonEdgers(UNITLIST, UNITNBRS): #all in-district boundary units that neighbor a non-district unit\n",
    "    ALLnonHDnbrs = set()\n",
    "    for UUU in UNITLIST:\n",
    "        ALLnonHDnbrs = ALLnonHDnbrs.union(set(UNITNBRS[UUU])).difference(set(UNITLIST))\n",
    "    BdryNonEdgerSet = set()\n",
    "    for UUU in UNITLIST:\n",
    "        if len(set(UNITNBRS[UUU]).intersection(ALLnonHDnbrs)) > 0:\n",
    "            BdryNonEdgerSet.add(UUU)\n",
    "    return list(BdryNonEdgerSet)\n",
    "\n",
    "def getEnclaveLists(UNITLIST, UNITNBRS):\n",
    "    \"\"\"\n",
    "    finds ALL units enclaved by a UNITLIST, parsed into lists of contiguous pieces\n",
    "    We assume the largest contiguous complement to the UNITLIST is not an enclave, but rather the majority of the HD complement\n",
    "    if the UNITLIST's complement (all couldBeEnclaved) is contiguous, the returned list will be blank\n",
    "    \"\"\"\n",
    "    eSets, nU = list(), len(UNITNBRS)\n",
    "    offmapList = list()\n",
    "    for i,L in enumerate(UNITNBRS):\n",
    "        if len(L) == 0:\n",
    "            offmapList.append(i)  #offmap list are units with no neighbors (were surrounded)\n",
    "    complementSet = set([i for i in range(nU)] ).difference( set(UNITLIST + offmapList) )    \n",
    "    remaining2nbrs = get2nbrs(UNITLIST, UNITNBRS)\n",
    "    \n",
    "    isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS) #quicker than contig check on entire complement\n",
    "    while not isContig:  #this will kick out before writing the final sublist = map majority\n",
    "        starter = shortList[0]\n",
    "        newEnclaveList = getContigFromStarter(starter, list(complementSet), UNITNBRS)\n",
    "        eSets.append(set(newEnclaveList))\n",
    "        remaining2nbrs = list(set(remaining2nbrs).difference(set(shortList)) )\n",
    "        isContig, shortList = isContiguous(remaining2nbrs,UNITNBRS)\n",
    "        \n",
    "        # couldBeEnclaved = list( set(couldBeEnclaved).difference(set(newEnclaveList)) )  #revised 18-Feb-24 -- was slower\n",
    "    fused_eSets = set()\n",
    "    for i, eSet in enumerate(eSets):\n",
    "        fused_eSets = fused_eSets.union(eSet)\n",
    "        for j in range(i+1, len(eSets) ) :\n",
    "            eSets[j] = eSets[j].difference(eSet)  #in case contiguity occurs, but not in 2-neighbor list; avoid double-count\n",
    "    remnant_eSet = complementSet.difference(fused_eSets) \n",
    "    eLengths = [len(eSet) for eSet in eSets]\n",
    "    if len(eSets) > 0:\n",
    "        if len(remnant_eSet) < np.max(eLengths):  #exchange the small remnant for the biggest found \"enclave\" (usually the major complement) \n",
    "            eSets[eLengths.index(np.max(eLengths))] = remnant_eSet.copy()\n",
    "    eLists = [list(eSet) for eSet in eSets]\n",
    "    return eLists\n",
    "\n",
    "def wontEnclave(proposedU, dList, NBRLIST, mapBDRYLIST):\n",
    "    \"\"\"\n",
    "    This method checks if adding a proposedU to a dList (list of units in a district) will create an \"enclave\" of units in the dList's complement\n",
    "    via two problems:  A) the dList will now have a discontiguous set of units on the map boundary.  The full map boundary list is mapBDRYLIST\n",
    "      B) The non-dList neighbors of dList units aren't contiguous\n",
    "    The method doesn't require that the dList wontEnclave without the proposedU included; it just checks the proposedU + dList combination\n",
    "    It also doesn't check that the dList is itself contiguous with or without proposedU\n",
    "    In that sense, it is more limited than enclaveCheck\n",
    "    \"\"\"\n",
    "    wontEnclave = True\n",
    "    newList, newSet = dList + [proposedU], set(dList + [proposedU])\n",
    "    unitsOnBoundary = list( set(mapBDRYLIST).intersection(newSet) )\n",
    "    wontEnclave, __ = isContiguous(unitsOnBoundary,NBRLIST)  #first check - does district touch MAP boundary in multiple places? (quick FAIL)\n",
    "    if wontEnclave: #slower check below for internal enclaves\n",
    "        adjoiners = get2nbrs(newList, NBRLIST)  #2-level to protect for queen adjacency in boundary        \n",
    "        wontEnclave, __ = isContiguous(adjoiners,NBRLIST)\n",
    "        if not wontEnclave:\n",
    "            nLoops = 1 #could be that fragmented adjoining districts are underestimating true contiguity.  Widen the contig search\n",
    "            maxLoops, ADJLIST = 6, adjoiners #unlike enclaveCheck, here we just arbitrarily set a number of loops for search expansion\n",
    "            while nLoops <= maxLoops and not wontEnclave:\n",
    "                nLoops +=1\n",
    "                adjSet = set(ADJLIST)  #align nomenclature w enclaveCheck\n",
    "                for UU in ADJLIST:\n",
    "                    adjSet = adjSet.union( set(NBRLIST[UU]).difference(set(newList)) )\n",
    "                ADJLIST = list(adjSet)\n",
    "                wontEnclave, __ =   isContiguous(ADJLIST, NBRLIST)\n",
    "        \n",
    "    return wontEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d041d328-83e0-45db-a869-e0956c23ee26",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the state postal code; e.g. OH  MN\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, enter 1 below to use mn_pl2020_vtd.dbf as this state's population data file\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "  1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempting to read in state unit geometries.  Stand by ...\n",
      "I read in the Census popn data. MN has 5706494 peeps and is divided into 4110 shapes.\n"
     ]
    }
   ],
   "source": [
    "STATE = str(input(\"Enter the state postal code; e.g. OH \")).upper()\n",
    "popFilename = STATE.lower()+\"_pl2020_vtd.dbf\"\n",
    "print(\"OK, enter 1 below to use\",popFilename,\"as this state's population data file\")\n",
    "enter1 = input(\" \")\n",
    "if int(enter1) != 1:\n",
    "    popFilename = input(\"OK, then enter the pop data file.  Typically a xx_pl2020_vtd.dbf\")\n",
    "print(\"attempting to read in state unit geometries.  Stand by ...\")\n",
    "tractPopFile = gpd.read_file(\"state_map_files/\"+popFilename)\n",
    "trueTractGeom = tractPopFile['geometry']\n",
    "nTracts = len(trueTractGeom)\n",
    "tractPop = tractPopFile['P0010001']\n",
    "statePop = np.sum(tractPop)\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "print(\"I read in the Census popn data.\",STATE,\"has\",statePop,\"peeps and is divided into\",nTracts,\"shapes.\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3bfdea9d-b0ea-497a-a556-6b488a3e333e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter the number of districts in the state.  My guess is 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 87 counties in MN .  I will assign them county Nos 0 - 86\n"
     ]
    }
   ],
   "source": [
    "tractGeom = trueTractGeom.copy()   #for some states, we will modify geom, so preserve original\n",
    "#tractNAME20 = tractPopFile['NAME20']\n",
    "tractPop = tractPopFile['P0010001']\n",
    "inputfileCountyNo = tractPopFile['COUNTYFP20']\n",
    "vtdGEOID20 =  tractPopFile['GEOID20'] \n",
    "nDistricts = int(round(statePop/760000,0))\n",
    "nCutDistricts = 0\n",
    "nDistricts = int(input(\"Enter the number of districts in the state.  My guess is \"+str(nDistricts)))\n",
    "tractArea = [tractGeom[t].area for t in range(nTracts)]\n",
    "trueTractCP =   [tractGeom[t].centroid for t in range(nTracts)]\n",
    "tractCP = trueTractCP.copy()  #for some states, we move secluded corners into the map, so save the true data\n",
    "tractCPx =  [tractCP[t].x for t in range(nTracts)]\n",
    "tractCPy =  [tractCP[t].y for t in range(nTracts)]\n",
    "inputCountyNumbers = list()\n",
    "for t in range(nTracts):\n",
    "    if inputfileCountyNo[t] not in inputCountyNumbers:\n",
    "        inputCountyNumbers.append(inputfileCountyNo[t])\n",
    "nCounties = len(inputCountyNumbers)\n",
    "print(\"There appear to be\",nCounties,\"counties in\",STATE,\".  I will assign them county Nos 0 -\",int(nCounties-1))\n",
    "sortedICNs = list(np.sort(inputCountyNumbers))\n",
    "countyNo = [sortedICNs.index(inputfileCountyNo[t]) for t in range(nTracts) ]\n",
    "\n",
    "isSkippedTract = [0] *nTracts  #this will house a temporary list of tracts for manipulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "adffc7a4-a78c-477f-8ea4-7f8e5109fa2a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now build the county-by-county geometries, hoping there are no islands\n",
      "Building county geom for county 0\n",
      "Building county geom for county 20\n",
      "Building county geom for county 40\n",
      "Building county geom for county 60\n",
      "Building county geom for county 80\n",
      "Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop < 4.5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There appear to be 4 unpopulated coastal tracts.  Lets plot them and their parent counties\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"We will now build the county-by-county geometries, hoping there are no islands\")\n",
    "skipList = list()  #a list of units we previously know to skip in the map\n",
    "isAlteredCounty = [False for c in range(nCounties)]\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "countyPop =       [0. for c in range(nCounties)]\n",
    "countyGeom =      [dummyPoly for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    if t not in skipList:\n",
    "        c = countyNo[t]\n",
    "        countyTractList[c].append(t)\n",
    "        countyPop[c] += tractPop[t]\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Building county geom for county\",c)\n",
    "    for t in countyTractList[c]:\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            countyGeom[c] = tractGeom[t]\n",
    "        else:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "origMAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    origMAP = origMAP.union(countyGeom[c])\n",
    "    if countyGeom[c] == dummyPoly:\n",
    "        print(\"WARNING! county\",c,\"is empty!\")\n",
    "    else:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "minTractPop = 4.5\n",
    "print(\"Here is your original county-based map b4 any triage; e.g eliminating coastal unpopulated tracts w pop <\",minTractPop)\n",
    "plt.show()\n",
    "if origMAP.geom_type == dummyPoly.geom_type:\n",
    "    mapExterior = origMAP.exterior\n",
    "else:\n",
    "    for i,geo in enumerate(origMAP.geoms):\n",
    "        if i == 0:\n",
    "            mapExterior = geo.exterior\n",
    "        else:\n",
    "            mapExterior = mapExterior.union(geo.exterior)\n",
    "\n",
    "for c in range(nCounties):\n",
    "    for t in countyTractList[c]:\n",
    "        if tractPop[t] < minTractPop:\n",
    "            if tractGeom[t].intersects(mapExterior):\n",
    "                isAlteredCounty[c] = True\n",
    "                skipList.append(t)\n",
    "print(\"There appear to be\",len(skipList),\"unpopulated coastal tracts.  Lets plot them and their parent counties\")\n",
    "for t in skipList:\n",
    "    plotPoly(tractGeom[t])\n",
    "    plotCenter(t,tractGeom[t],6)\n",
    "plotPoly(origMAP,0.2)\n",
    "for c in range(nCounties):\n",
    "    if isAlteredCounty[c]:\n",
    "        plotPoly(countyGeom[c])\n",
    "plt.show()\n",
    "trueMAP = origMAP  #use these terms interchangeably"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7a6c93c4-af08-47d5-90f7-dc0b4513aad5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Last chance to alter the skipList, otherwise the above 4 units will be axed\n",
      "here is the proposed skipList [3936, 359, 1874, 1703]\n",
      "here is the final skipList [3936, 359, 1874, 1703]\n"
     ]
    }
   ],
   "source": [
    "print(\"Last chance to alter the skipList, otherwise the above\",len(skipList),\"units will be axed\")\n",
    "print(\"here is the proposed skipList\", skipList)\n",
    "#skipList = [1939, 1364] #...  #alter here if needed - 1874, 1270, 1497, 1771 create contiguity problems if axed\n",
    "print(\"here is the final skipList\", skipList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "2989f381-466b-4882-bf1d-cfa37a7ba8ef",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I will now preserve the original county unit lists and geoms, then rebuild as needed\n",
      "removing coastal units from countyNo 15\n",
      "removing coastal units from countyNo 34\n",
      "removing coastal units from countyNo 37\n",
      "removing coastal units from countyNo 68\n",
      "Here is the revised state county map after eliminating coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Excellent!  We have no populated islands.  SKIP the below code block.\n",
      "we will scale longitudinal distance by 0.69179\n"
     ]
    }
   ],
   "source": [
    "print(\"I will now preserve the original county unit lists and geoms, then rebuild as needed\")\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "trueCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "for c in range(nCounties):\n",
    "    trueCountyTractList[c] = countyTractList[c].copy()\n",
    "    if isAlteredCounty[c]:\n",
    "        print(\"removing coastal units from countyNo\",c)\n",
    "        countyTractList[c] = list()\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in trueCountyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                countyTractList[c].append(t)\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "        if countyGeom[c] == dummyPoly:\n",
    "            print(\"Uh oh! county\",c,\"didn't have any usable tracts\")\n",
    "MAP = countyGeom[0]\n",
    "for c in range(nCounties):\n",
    "    plotPoly(countyGeom[c])\n",
    "    plotCenter(c,countyGeom[c])\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "origPopMAP = MAP   #origPopMAP is the map after eliminating coastal unpopulated tracts, with original islands\n",
    "print(\"Here is the revised state county map after eliminating coastal tracts\")\n",
    "plt.show()\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    print(\"Excellent!  We have no populated islands.  SKIP the below code block.\")\n",
    "else:\n",
    "    print(\"We appear to have some populated islands.  Separate out the main state geom in next block.\")\n",
    "LAT = MAP.centroid.y\n",
    "xScale = (1. - 1.089* abs(LAT/90)**1.9)\n",
    "print(\"we will scale longitudinal distance by\",r5(xScale))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8a562a21-4107-4a3c-a320-90442a473387",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\n",
      "unit 286 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 292 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 293 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 294 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 3112 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unit 1771 has island pieces.  We will reduce the tract to its main state component\n",
      "unit 1772 has island pieces.  We will reduce the tract to its main state component\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#RUN THIS ONLY IF WE FOUND POPULATED ISLANDS\n",
    "nSubGeoms = len(MAP.geoms)\n",
    "subGeoms = [MAP.geoms[n] for n in range(nSubGeoms)]\n",
    "subAreas = [subGeoms[n].area for n in range(nSubGeoms)]\n",
    "mainSubGeomNo = subAreas.index(np.max(subAreas))\n",
    "mainGeom = subGeoms[mainSubGeomNo]\n",
    "nonMainGeom = dummyPoly\n",
    "for geo in subGeoms:  #the \"nonMainGeom is all pieces of the state not in the biggest piece\n",
    "    if geo != mainGeom:\n",
    "        if nonMainGeom == dummyPoly:\n",
    "            nonMainGeom = geo\n",
    "        else:\n",
    "            nonMainGeom = nonMainGeom.union(geo)\n",
    "        \n",
    "print(\"Lets first identify which county each island belongs to.  Then we'll move the island to the closest county mainland\")\n",
    "hasIsland, isIsland = [False for c in range(nCounties)], [False for c in range(nCounties)]\n",
    "isIsland =  [False for t in range(nTracts)]\n",
    "islandXshift, islandYshift = [0. for t in range(nTracts)], [0. for t in range(nTracts)]\n",
    "islandList = list()\n",
    "for c in range(nCounties):\n",
    "    if countyGeom[c].intersects(nonMainGeom):  #this county contains an island.  Find all its island tracts\n",
    "        hasIsland[c] = True\n",
    "        if countyGeom[c].disjoint(mainGeom):  #need to connect the whole county\n",
    "            print(\"county\",c,\"is completely disconnected from mainland.  Move it to adjoin mainland\")\n",
    "            isIsland[c] = True\n",
    "            countyDist = [999999. for cc in range(nCounties)]  #default, to avoid picking island counties as closest to this one\n",
    "            for cc in range(nCounties):\n",
    "                if countyGeom[cc].intersects(mainGeom):\n",
    "                    countyDist[cc] = countyGeom[c].distance(countyGeom[cc].intersection(mainGeom) )\n",
    "            closestCounty = countyDist.index(np.min(countyDist))\n",
    "            p1, p2 = nearest_points(countyGeom[closestCounty],countyGeom[c])\n",
    "            for t in countyTractList[c]:\n",
    "                islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "            for t in countyTractList[c]:\n",
    "                plotPoly(tractGeom[t])\n",
    "                plotCenter(t,tractGeom[t])\n",
    "                plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                tractCP[t] = tractGeom[t].centroid\n",
    "                tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                plotPoly(tractGeom[t],0.2)\n",
    "        else: #move only the county's island tracts to connect with main geom\n",
    "            mainCountyGeom = countyGeom[c].intersection(mainGeom)\n",
    "            plotPoly(mainCountyGeom)\n",
    "            plotCenter(c,mainCountyGeom)\n",
    "            for t in countyTractList[c]:\n",
    "                if tractGeom[t].intersects(nonMainGeom) and t not in skipList:\n",
    "                    if tractGeom[t].intersects(mainCountyGeom):\n",
    "                        print(\"unit\",t,\"has island pieces.  We will reduce the tract to its main state component\")\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "                        tractGeom[t] = tractGeom[t].intersection(mainCountyGeom)\n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                    else:    \n",
    "                        isIsland[t] = True\n",
    "                        print(\"unit\",t,\"is a true island.  We will move it to adjoin the mainland in same county.\")\n",
    "                        islandList.append(t)\n",
    "                        if tractGeom[t].geom_type != dummyPoly.geom_type :  #island tract is multiple geoms.  collapse to its largest isle\n",
    "                            isleGeos = [geo for geo in tractGeom[t].geoms]\n",
    "                            isleAreas = [geo.area for geo in isleGeos]\n",
    "                            biggestIsleNo = isleAreas.index(np.max(isleAreas))\n",
    "                            tractGeom[t] = isleGeos[biggestIsleNo]\n",
    "                            tractCP[t] = tractGeom[t].centroid\n",
    "                        p1, p2 = nearest_points(mainCountyGeom, tractGeom[t])\n",
    "                        islandXshift[t], islandYshift[t]  = p1.x - p2.x , p1.y - p2.y\n",
    "                        plotPoly(tractGeom[t])\n",
    "                        plotCenter(t,tractGeom[t])\n",
    "                        plt.arrow(tractCP[t].x, tractCP[t].y,islandXshift[t], islandYshift[t])\n",
    "                        tractGeom[t] = translate(tractGeom[t], xoff=islandXshift[t], yoff=islandYshift[t])                   \n",
    "                        tractCP[t] = tractGeom[t].centroid\n",
    "                        tractCPx[t], tractCPy[t] = tractCP[t].x, tractCP[t].y\n",
    "                        plotPoly(tractGeom[t],0.2)\n",
    "        plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "9a94118d-5863-4458-b77a-67d18cf01c2c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\n",
      "This would need adjustment for multi-county islands like Michigan UP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing with island triage - RUN ONLY WITH ISLANDS\n",
    "print(\"If you like my proposed translations, let's rebuild the MAP with the adjusted county geoms\")\n",
    "print(\"This would need adjustment for multi-county islands like Michigan UP\")\n",
    "for c in range(nCounties):\n",
    "    if hasIsland[c] :  #rebuild the county geom with the translated islands\n",
    "        countyGeom[c] = dummyPoly\n",
    "        for t in countyTractList[c]:\n",
    "            if t not in skipList:\n",
    "                if countyGeom[c] == dummyPoly:\n",
    "                    countyGeom[c] = tractGeom[t]\n",
    "                else:\n",
    "                    countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "MAP = countyGeom[0]\n",
    "plotPoly(countyGeom[0])\n",
    "for c in range(1,nCounties):\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "    plotPoly(countyGeom[c])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "4aebe4ee-ee7b-4bf3-8413-f315556d453e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "computing all county centerpoints, then plot them\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"computing all county centerpoints, then plot them\")\n",
    "countyCP  = list()\n",
    "cutCountyList = list()\n",
    "for c in range(nCounties):\n",
    "    cTL = countyTractList[c]\n",
    "    countyCP.append(getHDcp( [tractCP[v] for v in cTL], [tractPop[v] for v in cTL], [i for i in range(len(cTL) ) ] ) )\n",
    "    if countyCP[c].disjoint(countyGeom[c]):  #possible with weird-shaped county\n",
    "        countyCP[c] = nearest_points(countyGeom[c],countyCP[c])[0]\n",
    "    plotPoly(countyCP[c].buffer(0.03))\n",
    "    plotPoly(countyGeom[c],0.5)\n",
    "plotPoly(MAP)\n",
    "plt.show()   \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "207f3a55-e361-4777-ae46-41fe3d54a4b8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This code block reads in a csv with whole districts to be cut out of the map\n",
      "For MN my input file says to cut out 0 districts out of 8\n",
      "There were no cut districts in MN\n"
     ]
    }
   ],
   "source": [
    "print(\"This code block reads in a csv with whole districts to be cut out of the map\")\n",
    "unclippedMAP = MAP\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "nCutDistricts = nCuts\n",
    "nStops = trimDF[\"nStopLines\"][DFrow]\n",
    "nDistricts = trimDF[\"nDistricts\"][DFrow]\n",
    "stopLines = list()  #the 'stoplines' stop wedge growth that hops across concave map areas (not currently used)\n",
    "cutCountyList = list()\n",
    "allCutLists, allCutPops = list(), list()\n",
    "print(\"For\",STATE,\"my input file says to cut out\",nCuts,\"districts out of\",nDistricts)\n",
    "if nCuts > 0:\n",
    "    cutList = list()\n",
    "    cutXs = ast.literal_eval(trimDF[\"cutXs\"][DFrow])\n",
    "    cutYs = ast.literal_eval(trimDF[\"cutYs\"][DFrow])\n",
    "    cutPoints = [Point(cutXs[i],cutYs[i]) for i in range(len(cutXs)) ]\n",
    "    for cutNo in range(nCuts):\n",
    "        print(\"performing cut no\",cutNo,\"for state\",STATE)  #first two cutPoints must form the cutLine\n",
    "        cutNotDone = True\n",
    "        thisCutPoints = [ cutPoints[int(4*cutNo)],cutPoints[int(4*cutNo+1)],cutPoints[int(4*cutNo+2)],cutPoints[int(4*cutNo+3)]  ]\n",
    "        while cutNotDone:\n",
    "            cutPoly = Polygon([thisCutPoints[0],thisCutPoints[1],thisCutPoints[2],thisCutPoints[3] ])\n",
    "            cutLine = LineString([thisCutPoints[0], thisCutPoints[1] ] )\n",
    "            cutList = list()\n",
    "            cutPop = 0.\n",
    "            for c in range(nCounties):\n",
    "                if cutPoly.intersects(countyGeom[c]):\n",
    "                    if cutPoly.contains(countyGeom[c]):\n",
    "                        cutList = cutList + countyTractList[c]\n",
    "                        cutPop += countyPop[c]\n",
    "                    else:\n",
    "                        for t in countyTractList[c]:\n",
    "                            if cutPoly.contains(tractCP[t]):\n",
    "                                cutList.append(t)\n",
    "                                cutPop += tractPop[t]\n",
    "            print(\"the total proposed cutPop is\",cutPop,\". Compare to\",int(statePop/nDistricts) )\n",
    "\n",
    "            doIcut = input(\"enter 1 to apply the cut\")\n",
    "            if str(doIcut) == str(1):\n",
    "                cutNotDone = False\n",
    "                allCutLists.append(cutList)\n",
    "                allCutPops.append(cutPop)\n",
    "            else:\n",
    "                print(\"Here is the state and the last proposed cutPoly.\")\n",
    "                plotPoly(cutPoly)\n",
    "                plotPoly(MAP)\n",
    "                plt.show()\n",
    "                print(cutPoly)\n",
    "                oldPts = list(cutPoly.exterior.coords)\n",
    "                newPtXs = ast.literal_eval(input(\"enter alternate [ x0, x1 ] for the first two points\") )\n",
    "                newPtYs = ast.literal_eval(input(\"enter alternate [ y0, y1 ] for the first two points\") )\n",
    "                thisCutPoints = [Point(newPtXs[0],newPtYs[0]), Point(newPtXs[1],newPtYs[1]),oldPts[2], oldPts[3] ]\n",
    "allCutVTDs = list()\n",
    "for L in allCutLists:\n",
    "    for v in L:\n",
    "        allCutVTDs.append(v)\n",
    "if nCutDistricts == 0:\n",
    "    print(\"There were no cut districts in\",STATE)\n",
    "else:\n",
    "    print(\"here are your cut districts\")\n",
    "    plotPoly(MAP)\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        cutGeo = tractGeom[L[0]]\n",
    "        for v in L:\n",
    "            cutGeo=cutGeo.union(tractGeom[v])\n",
    "        plotPoly(cutGeo,2)\n",
    "        plotCenter(i,cutGeo)\n",
    "        plotCenter(allCutPops[i],Point(cutGeo.centroid.x,cutGeo.centroid.y-0.5) )\n",
    "    plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "4c915415-6c44-4c43-9826-b565cebed95a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Write the vtd cutlists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Write the vtd cutlists to a file\")\n",
    "cutDistrictNo = list()\n",
    "for v in allCutVTDs:\n",
    "    for i,L in enumerate(allCutLists):\n",
    "        if v in L:\n",
    "            cutDistrictNo.append(i)\n",
    "            break\n",
    "nbrDF = pd.DataFrame( {\"vtdNo\":allCutVTDs,\"cutDistrictNo\":cutDistrictNo} )\n",
    "outname = STATE+\"wholeDistrictCuts.csv\" \n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "nbrDF.to_csv(outpath)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "17721728-e5c0-4787-b430-9d7d94970667",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "countyPop = [0. for c in range(nCounties)]\n",
    "for t in range(nTracts):\n",
    "    countyPop[countyNo[t]] += tractPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "02f95c46-5073-4b9d-817c-16a57d5ebb52",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "8\n"
     ]
    }
   ],
   "source": [
    "print(nDistricts)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "f3073320-8d92-45ba-beb2-fb8c08d7170d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Removed all whole districts.  Finalize stats before squishing in outcroppings.\n",
      "Of the total statePop 5706494.0 we ignore 0.0 as it is cut out of the map\n",
      "This excluded pop comes from a total of 4 tracts\n",
      "Our final adjusted number of state districts, excluded fixed cut-out is 8 rather than original 8\n",
      "Each district will be drawn to house 713311.75 = 1/ 8 of non-cutout state pop 5706494.0 vs original= 5706494.0\n",
      "Here is a county-level modified map with each county's fraction of a district pop\n",
      "working on county 0\n",
      "working on county 20\n",
      "working on county 40\n",
      "working on county 60\n",
      "working on county 80\n",
      "here is the MN map excluding cut and unpop coastal tracts\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Removed all whole districts.  Finalize stats before squishing in outcroppings.\")\n",
    "trueCountyPop = [countyPop[c] for c in range(nCounties)]\n",
    "trueCountyGeom = countyGeom.copy()\n",
    "countyPop = [0. for c in range(nCounties)]\n",
    "trueStatePop, true_nDistricts = np.sum(trueCountyPop), nDistricts\n",
    "trueCountyTractList = [list() for c in range(nCounties)]\n",
    "# minTractPop = 4.5  #already defined above\n",
    "populatedTractList = list()\n",
    "countyTractList = [list() for c in range(nCounties)]\n",
    "statePop, excludedPop = 0., 0.\n",
    "\n",
    "for t in range(nTracts):\n",
    "    trueCountyTractList[countyNo[t]].append(t)\n",
    "    if t in allCutVTDs or t in skipList:  #  or vtdPop[t] < minTractPop:  #need to keep low-pop vtds as VEST may have assigned votes to them\n",
    "        excludedPop += tractPop[t]\n",
    "    else:\n",
    "        populatedTractList.append(t)\n",
    "        countyTractList[countyNo[t]].append(t)\n",
    "        countyPop[countyNo[t]] += tractPop[t]\n",
    "        statePop += tractPop[t]\n",
    "        #tractPop[t] = max(tractPop[t],0.000001)  #avoid possible later div/zero errors for nil-vote vtds\n",
    "print(\"Of the total statePop\",statePop+excludedPop,\"we ignore\",excludedPop,\"as it is cut out of the map\") #,\n",
    "#\"or in sparsely populated areas (<\",minTractPop,\") per geom\")\n",
    "print(\"This excluded pop comes from a total of\",nTracts -len(populatedTractList),\"tracts\")\n",
    "true_nDistricts = nDistricts\n",
    "nDistricts -= nCutDistricts\n",
    "print(\"Our final adjusted number of state districts, excluded fixed cut-out is\",nDistricts,\"rather than original\",true_nDistricts)\n",
    "aDP = statePop/float(nDistricts)\n",
    "print(\"Each district will be drawn to house\",r3(aDP),\"= 1/\",nDistricts,\"of non-cutout state pop\",statePop,\"vs original=\",trueStatePop)\n",
    "print(\"Here is a county-level modified map with each county's fraction of a district pop\")\n",
    "\n",
    "vtdGeom = tractGeom.copy()\n",
    "nVTDs = len(vtdGeom)\n",
    "\n",
    "cutCountyList, uncutCountyList = list(), list()\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"working on county\",c)\n",
    "    if len(countyTractList[c]) == 0:  #no vtds added to county b/c all were in cut lists:\n",
    "        cutCountyList.append(c)\n",
    "    else:\n",
    "        uncutCountyList.append(c)\n",
    "        countyGeom[c] = tractGeom[countyTractList[c][0]]\n",
    "        for t in countyTractList[c]:\n",
    "            countyGeom[c] = countyGeom[c].union(tractGeom[t])\n",
    "uncutMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "print(\"here is the\",STATE,\"map excluding cut and unpop coastal tracts\")\n",
    "\n",
    "for c in uncutCountyList:\n",
    "    plotPoly(countyGeom[c])\n",
    "    FONTSIZE = 11\n",
    "    if countyPop[c] / statePop < 0.02:\n",
    "        FONTSIZE = 7\n",
    "        plotCenter(r3(countyPop[c]/aDP),countyGeom[c], FONTSIZE)\n",
    "    else:\n",
    "        plotCenter(round(countyPop[c]/aDP,2),countyGeom[c], FONTSIZE)\n",
    "plotPoly(trueMAP,0.1)\n",
    "for c in cutCountyList:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "    plotCenter(\"cut\",countyGeom[c],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "0062ac21-3328-4616-99ed-70c53e62b308",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the map topology before any squish operations.  Plot countyPop/aDP\n",
      "Working on county  0 distances\n",
      "Working on county  20 distances\n",
      "Working on county  40 distances\n",
      "Working on county  60 distances\n",
      "Working on county  80 distances\n",
      "the max LAT-scaled distance between counties is 6.222\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter user-picked max district diameter, or 0 to accept 6.222  0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Working on county  0 neighbors\n",
      "Working on county  20 neighbors\n",
      "Working on county  40 neighbors\n",
      "Working on county  60 neighbors\n",
      "Working on county  80 neighbors\n",
      "I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#For corners and outcroppings, we fuse county clusters\n",
    "print(\"Now finalize the map topology before any squish operations.  Plot countyPop/aDP\")\n",
    "preSquishCountyGeom = [countyGeom[c] for c in range(nCounties)]\n",
    "maxD = 0.\n",
    "for c in range(nCounties):\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"distances\")\n",
    "    if c not in cutCountyList:\n",
    "        plotPoly(countyGeom[c],0.2)\n",
    "        plotCenter(r3(countyPop[c]/aDP), countyGeom[c], 7 )\n",
    "        for cc in range(c+1, nCounties):\n",
    "            dist = getLongDist(countyCP[c],countyCP[cc],xScale)\n",
    "            if dist > maxD and cc not in cutCountyList:\n",
    "                maxD = dist\n",
    "                #print(c,cc,maxD)\n",
    "print(\"the max LAT-scaled distance between counties is\",r5(maxD))\n",
    "plotPoly(MAP)\n",
    "plotPoly(MAP.centroid.buffer(0.5*maxD))\n",
    "plt.show()\n",
    "inputD = float( input(\"enter user-picked max district diameter, or 0 to accept \"+str(r5(maxD))+\" \") )\n",
    "if inputD > 0:\n",
    "    maxD = inputD\n",
    "neighborCountyList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"Working on county \",c,\"neighbors\")\n",
    "    for cc in uncutCountyList:\n",
    "        if cc > c and cc not in cutCountyList:  \n",
    "            if countyGeom[c].intersects(countyGeom[cc]) :\n",
    "                neighborCountyList[c].append(cc)\n",
    "                neighborCountyList[cc].append(c)\n",
    "print(\"I have also identified each county's neighbors.  Let's visualize the counties with two or fewer neighbors\")\n",
    "hasFewNeighborCs, has1neighborCs = list(), list()\n",
    "plotPoly(MAP,0.15)\n",
    "for c in uncutCountyList:\n",
    "    if len(neighborCountyList[c]) == 2:\n",
    "        hasFewNeighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.2,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.5)\n",
    "    if len(neighborCountyList[c]) < 2:\n",
    "        has1neighborCs.append(c)\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c+0.1,countyGeom[c])\n",
    "        for cc in neighborCountyList[c] :\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "plt.show()   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "f9b3df93-d821-44ca-b4f4-b65d13baaffb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "continuing from above, develop corner county blocks from each low-pop corner county until it hits 0.25 of 713311\n",
      "checking if county 15 with pop 5600.0 and only 1 neighbor is less pop than 178327 vs districtPop 713311\n",
      "checking if county 27 with pop 18843.0 and 1 or 2 neighbors is less pop than 178327\n",
      "checking if county 34 with pop 4207.0 and 1 or 2 neighbors is less pop than 178327\n",
      "checking if county 37 with pop 10905.0 and 1 or 2 neighbors is less pop than 178327\n",
      "checking if county 62 with pop 3935.0 and 1 or 2 neighbors is less pop than 178327\n",
      "checking if county 15 with pop 5600.0 and 1 or 2 neighbors is less pop than 178327\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Below I plot these again by county no, with faded neighboring counties\n",
      "0   [27, 84, 22, 78, 49, 19]\n",
      "1   [34, 44, 67, 56, 59, 38, 3, 62, 53, 43, 14, 28]\n",
      "2   [37, 15]\n",
      "3   [62, 56, 59, 44, 43, 53, 14, 3, 67, 2]\n",
      "4   [15, 37]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are 713311.75 178327\n",
      "You may suggest [ [27, 84, 22, 78, 54, 49], [34, 67, 44, 38, 3, 56, 62, 59, 14, 53, 43], [15, 37, 68], [66, 58, 52, 40, 50, 31] ] \n",
      "let's decide whether to delete, accept, or modify list [27, 84, 22, 78, 49, 19] with pop 172025.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [27, 84, 22, 78, 54, 49]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [27, 84, 22, 78, 49, 19] with [27, 84, 22, 78, 54, 49]\n",
      "let's decide whether to delete, accept, or modify list [34, 44, 67, 56, 59, 38, 3, 62, 53, 43, 14, 28] with pop 169408.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [34, 67, 44, 38, 3, 56, 62, 59, 14, 53, 43]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [34, 44, 67, 56, 59, 38, 3, 62, 53, 43, 14, 28] with [34, 67, 44, 38, 3, 56, 62, 59, 14, 53, 43]\n",
      "let's decide whether to delete, accept, or modify list [37, 15] with pop 16505.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) [15, 37, 68]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OK, I will replace [37, 15] with [15, 37, 68]\n",
      "let's decide whether to delete, accept, or modify list [62, 56, 59, 44, 43, 53, 14, 3, 67, 2] with pop 175277.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's decide whether to delete, accept, or modify list [15, 37] with pop 16505.0\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list) 0\n",
      "enter 1 if you want to manually add another corner-county cluster 1\n",
      "Type in a [county list], where the corner county is first in the list.  Or type 0 to stop [66, 58, 52, 40, 50, 31]\n",
      "enter 1 if you want to manually add another corner-county cluster 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Our final pops and fused-county lists are...\n",
      "314005.0 [27, 84, 22, 78, 54, 49]\n",
      "148064.0 [34, 67, 44, 38, 3, 56, 62, 59, 14, 53, 43]\n",
      "216736.0 [15, 37, 68]\n",
      "65226.0 [66, 58, 52, 40, 50, 31]\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "aDP = float(statePop)/nDistricts\n",
    "maxCCBratio = 1./4.  #adjustable max fraction of district pop for corner county blocks.  Let's try 3/16\n",
    "maxCCBpop = maxCCBratio * aDP\n",
    "print(\"continuing from above, develop corner county blocks from each low-pop corner county until it hits\",r3(maxCCBratio),\"of\",int(aDP) )\n",
    "CCBlist, CCBpop, passThruList = list(), list(), list()  #\"waiveThru\" counties get chance to join a cluster even if high pop\n",
    "nFuses = 0\n",
    "for c in has1neighborCs:\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and only 1 neighbor is less pop than\",int(maxCCBpop),\"vs districtPop\",int(aDP) )\n",
    "    if countyPop[c] > maxCCBpop:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        nc = neighborCountyList[c][0]\n",
    "        plotPoly(countyGeom[nc],0.5)\n",
    "        plotPoly(MAP,0.2)\n",
    "        print(\"county\",c,\"has pop\",countyPop[c],\"and its only neighbor has pop\",countyPop[nc],\"vs districtPop\",aDP,\". Default = keep un-fused\")\n",
    "        print(\"enter 0 to keep\",c,\"as an unfused collection of units, 1 to fuse as one unit and stop, 2 to force-add at least the next closest county\")\n",
    "        fuseChoice = input(\"0, 1, or 2.  Any other input taken as a zero\")\n",
    "        if fuseChoice == 0:\n",
    "            keepUnfused = True\n",
    "            break\n",
    "        elif int(fuseChoice) == 1:\n",
    "            CCBlist.append([c])\n",
    "            CCBpop.append(countyPop[c])  \n",
    "            hasFewNeighborCs.append(c)  #this adds this [c] to the final list of fused units, but will fail to find more in below\n",
    "        elif int(fuseChoice) == 2:\n",
    "            CCBlist.append([c,nc ] )\n",
    "            CCBpop.append(countyPop[c] + countyPop[nc])\n",
    "            hasFewNeighborCs.append(c)\n",
    "            passThruList.append(c)   #pass on thru to the below 2neighbor logic even if too high-pop to qualify\n",
    "    else:\n",
    "        hasFewNeighborCs.append(c)  #normal case; we'll handle in next, more general, for loop            \n",
    "        \n",
    "for c in hasFewNeighborCs:\n",
    "    print(\"checking if county\",c,\"with pop\",countyPop[c],\"and 1 or 2 neighbors is less pop than\",int(maxCCBpop) )\n",
    "    if countyPop[c] < maxCCBpop :\n",
    "        CCBlist.append([c])\n",
    "        CCBpop.append(countyPop[c])\n",
    "        CCBno = CCBlist.index([c])\n",
    "    if c in passThruList:\n",
    "        CCBno = CCBlist.index([c,neighborCountyList[c][0] ])\n",
    "    if countyPop[c] < maxCCBpop or c in passThruList:            \n",
    "        CCBstarter = c\n",
    "        canAdd = True\n",
    "        while canAdd:\n",
    "            nbrSet = set()\n",
    "            for cc in CCBlist[CCBno]:\n",
    "                nbrSet = ( nbrSet.union(set(neighborCountyList[cc])) ).difference(set(CCBlist[CCBno]))\n",
    "            nPop = [countyPop[cc] for cc in nbrSet]\n",
    "            nDist = [countyGeom[cc].centroid.distance(countyGeom[CCBstarter].centroid) for cc in nbrSet]\n",
    "            idx = np.argsort(nDist)\n",
    "            nbrList, newList = list(nbrSet), list()\n",
    "            for i in range(len(nDist)):  #add counties, closest to starter that will fit until over\n",
    "                cc = nbrList[idx[i]]\n",
    "                if CCBpop[CCBno] + countyPop[cc] < maxCCBpop:\n",
    "                    newList.append(cc)\n",
    "                    CCBlist[CCBno].append(cc)\n",
    "                    CCBpop[CCBno] += countyPop[cc]\n",
    "                    #print(\"adding county\",cc,\"with pop\",countyPop[cc],\"to list started by\",CCBstarter,\".Cluster pop now\",CCBpop[CCBno]  )\n",
    "            if newList == list():  #no eligible neighbor counties found; stop\n",
    "                canAdd = False\n",
    "                for cc in CCBlist[CCBno]:\n",
    "                    plotPoly(countyGeom[cc])\n",
    "                    plotCenter(CCBno,countyGeom[cc])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "                    \n",
    "print(\"Below I plot these again by county no, with faded neighboring counties\")\n",
    "plotPoly(MAP,0.15)\n",
    "for L in CCBlist:\n",
    "    print(CCBlist.index(L),\" \",L)\n",
    "    for c in L:\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(c,countyGeom[c])\n",
    "        for cc in list(set(neighborCountyList[c]).difference(L) ):\n",
    "            plotPoly(countyGeom[cc],0.4)\n",
    "            plotCenter(cc,countyGeom[cc],8)\n",
    "plt.show()\n",
    "rejectList = list()\n",
    "print(\"Now finalize the corner lists.  Remember, our avgDistrictPop and normal pop threshold are\",r3(aDP), int(maxCCBpop))\n",
    "print(\"You may suggest [ [27, 84, 22, 78, 54, 49], [34, 67, 44, 38, 3, 56, 62, 59, 14, 53, 43], [15, 37, 68], [66, 58, 52, 40, 50, 31] ] \" )\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if L[0] not in passThruList:  #if we forced the fused-counties list above, don't give option here to modify\n",
    "        print(\"let's decide whether to delete, accept, or modify list\",L,\"with pop\",CCBpop[i] )\n",
    "        isOK = input(\"enter 0 to ax, 1 to accept, or type in a [replacement list] (must start with same c as orig list)\")\n",
    "        if not (isOK == 1 or isOK == str(1)) :\n",
    "            if isOK == 0 or isOK == str(0) :\n",
    "                rejectList.append(L)\n",
    "            else:\n",
    "                notGood = True\n",
    "                while notGood:       \n",
    "                    Lnew = ast.literal_eval(isOK)        \n",
    "                    if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                        notGood = False\n",
    "                    else:\n",
    "                        print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                        isOK = input(\"Try again here \")\n",
    "                print(\"OK, I will replace\",L,\"with\",Lnew)\n",
    "                CCBpop[i] = np.sum( [countyPop[c] for c in Lnew] )\n",
    "                CCBlist[i] = Lnew.copy()\n",
    "for L in rejectList:\n",
    "    del CCBpop[ CCBlist.index(L)]\n",
    "    del CCBlist[CCBlist.index(L)]\n",
    "stillAdding = True\n",
    "while stillAdding:\n",
    "    addMore = input(\"enter 1 if you want to manually add another corner-county cluster\")\n",
    "    if int(addMore) != 1:\n",
    "        stillAdding = False\n",
    "    else:\n",
    "        isOK = input(\"Type in a [county list], where the corner county is first in the list.  Or type 0 to stop\")\n",
    "        if isOK == 0 or isOK == str(0) :\n",
    "            print(\"OK, we'll stop adding corner clusters\")\n",
    "            stillAdding = False\n",
    "        else:\n",
    "            notGood = True\n",
    "            while notGood:       \n",
    "                Lnew = ast.literal_eval(isOK)        \n",
    "                if len(list(set(Lnew).difference(set([c for c in range(nCounties) ] )))) == 0:\n",
    "                    notGood = False\n",
    "                    for L in CCBlist:\n",
    "                        if set(L).intersection(set(Lnew)) != set(list()) :\n",
    "                            notGood = True\n",
    "                            print(\"OOPS! The following inputted counties are already in\",L,\":\",set(L).intersection(set(Lnew)) )\n",
    "                            isOK = input(\"Try again here \")\n",
    "                    if notGood == False:\n",
    "                        CCBlist.append(Lnew)\n",
    "                        CCBpop.append( np.sum( [countyPop[c] for c in Lnew] ) )\n",
    "                else:\n",
    "                    print(\"Oops!  You didn't enter a valid list.  Try again as [\",L[0],\", n1, n2, ... ] where n1, n2 are county integers\")\n",
    "                    isOK = input(\"Try again here \")\n",
    "print(\"Our final pops and fused-county lists are...\")\n",
    "allFusedCounties = list()\n",
    "CCBgeom = [dummyPoly for L in CCBlist ]\n",
    "CCBcp = list()\n",
    "for i, L in enumerate(CCBlist):\n",
    "    CCBcp.append( getHDcp([countyCP[c] for c in L], [countyPop[c] for c in L], [ j for j in range(len(L)) ] ) )\n",
    "    print(CCBpop[i],L)\n",
    "    pops, CPs = list(), list()\n",
    "    for c in L:\n",
    "        if c == L[0]:\n",
    "            CCBgeom[i] = countyGeom[c]\n",
    "        else:\n",
    "            CCBgeom[i] = CCBgeom[i].union(countyGeom[c])\n",
    "        allFusedCounties.append(c)\n",
    "        pops += countyPop[c]       #  IS THIS EVEN USED?\n",
    "        CPs.append(countyCP[c])   #  IS THIS EVEN USED?\n",
    "        plotPoly(countyGeom[c])\n",
    "        plotCenter(i,countyGeom[c])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "206c9372-8ec8-4190-93ed-04df286466e0",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now identify the border counties + border fused units, and interior small counties with pop < 14266\n",
      "We defined a total of 15 unit (but not corner-cluster) counties in the map, excluding the cut-out districts\n"
     ]
    }
   ],
   "source": [
    "maxWholeBorderCountyPop = 0.02 * aDP   #to encourage contiguity, border counties > 0.02 aDP will be forced whole\n",
    "maxInteriorBorderCountyPop = 0.02 * aDP\n",
    "print(\"now identify the border counties + border fused units, and interior small counties with pop <\", int(maxInteriorBorderCountyPop))\n",
    "unitCounties, borderCounties = list(), list()\n",
    "origMAP = MAP\n",
    "if MAP.geom_type == dummyPoly.geom_type:\n",
    "    MAPexterior = MAP.exterior\n",
    "else:\n",
    "    maxArea = 0\n",
    "    for geo in MAP.geoms:\n",
    "        if geo.area > maxArea:\n",
    "            MAPexterior = geo.exterior\n",
    "            maxArea = geo.area\n",
    "            MAP0 = geo\n",
    "    MAP = MAP0\n",
    "for c in uncutCountyList:\n",
    "    if countyGeom[c].intersects(MAPexterior):\n",
    "        borderCounties.append(c)\n",
    "        if c not in allFusedCounties:\n",
    "            if countyPop[c] < maxWholeBorderCountyPop:\n",
    "                unitCounties.append(c)\n",
    "    else:\n",
    "        if countyPop[c] < maxInteriorBorderCountyPop and c not in allFusedCounties:\n",
    "            unitCounties.append(c)\n",
    "print(\"We defined a total of\",len(unitCounties),\"unit (but not corner-cluster) counties in the map, excluding the cut-out districts\")        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "e0ff719c-59dc-4827-a522-11bd352f7524",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For this state, do we have a lot of populated fragmented VTDs?\n",
      "249 fragmented VTDs out of 4110\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FYI, here are the locations of fragmented VTDs with pop > 3000\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"For this state, do we have a lot of populated fragmented VTDs?\")\n",
    "nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "print(len(fragmentedVTDs),\"fragmented VTDs out of\",nVTDs)\n",
    "fragPop = [tractPop[v] for v in fragmentedVTDs]\n",
    "plt.hist(fragPop)\n",
    "plt.show()\n",
    "print(\"FYI, here are the locations of fragmented VTDs with pop > 3000\")\n",
    "for v in fragmentedVTDs:\n",
    "    if tractPop[v] > 3000:\n",
    "        plotPoly(vtdGeom[v])\n",
    "plotPoly(MAP,0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "71d771f8-dbe2-48f9-a702-9f66a62d1174",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\n",
      "I split up 249 fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\n",
      "looking for surrounds, now working on vtd 0\n",
      "looking for surrounds, now working on vtd 501\n",
      "looking for surrounds, now working on vtd 1001\n",
      "looking for surrounds, now working on vtd 1501\n",
      "looking for surrounds, now working on vtd 2003\n",
      "looking for surrounds, now working on vtd 2503\n",
      "looking for surrounds, now working on vtd 3003\n",
      "looking for surrounds, now working on vtd 3503\n",
      "looking for surrounds, now working on vtd 4004\n",
      "On loop 2 for county 0  we found that vtd frag 4211 now has only 1 neighbor 4212\n",
      "On loop 2 for county 24  we found that vtd frag 1079 now has only 1 neighbor 4256\n",
      "On loop 2 for county 23  we found that vtd frag 1407 now has only 1 neighbor 4338\n",
      "On loop 2 for county 72  we found that vtd frag 4389 now has only 1 neighbor 4390\n",
      "On loop 2 for county 72  we found that vtd frag 1911 now has only 1 neighbor 4424\n",
      "On loop 2 for county 42  we found that vtd frag 4502 now has only 1 neighbor 4505\n",
      "On loop 2 for county 42  we found that vtd frag 4503 now has only 1 neighbor 4505\n",
      "On loop 2 for county 63  we found that vtd frag 2540 now has only 1 neighbor 4520\n",
      "On loop 2 for county 72  we found that vtd frag 4564 now has only 1 neighbor 4568\n",
      "On loop 2 for county 9  we found that vtd frag 3892 now has only 1 neighbor 4619\n",
      "After surround checks, we appear to have 2729 building blocks defined. We captured 444 surrounded VTDs\n",
      "working on unit neighbor lists for county 0\n",
      "WARNING - unit 717  = vtd 1268 in county 6 has only 1 neighbor= [667] . Optional triage in next block\n",
      "WARNING - unit 718  = vtd 4325 in county 6 has only 1 neighbor= [667] . Optional triage in next block\n",
      "WARNING - unit 18  = vtd 3 in county 7 has only 1 neighbor= [16] . Optional triage in next block\n",
      "working on unit neighbor lists for county 20\n",
      "working on unit neighbor lists for county 40\n",
      "WARNING - unit 2437  = vtd 3690 in county 45 has only 1 neighbor= [2419] . Optional triage in next block\n",
      "WARNING - unit 959  = vtd 1553 in county 55 has only 1 neighbor= [927] . Optional triage in next block\n",
      "WARNING - unit 933  = vtd 1525 in county 55 has only 1 neighbor= [855] . Optional triage in next block\n",
      "working on unit neighbor lists for county 60\n",
      "working on unit neighbor lists for county 80\n",
      "All done creating unit lists\n"
     ]
    }
   ],
   "source": [
    "#3/2/24 - split up all multipoly VTDs into fragments, divvy pop by area\n",
    "unitPop, unitCP, unitGeom, nbrUnitGeom, allUnits = list(), list(), list(), list(), list()\n",
    "vtdUnits, countyUnits, borderUnits = list(),list(),list()\n",
    "countyUnitList = [list() for c in range(nCounties) ]\n",
    "surroundedVTDs, surrounders = list(), list()  #vtds that are surrounded by another vtd - problem for later enclaves, xfer their pops to surrounders\n",
    "#These surrounded VTDs don't get transferred to the unit list\n",
    "print(\"Now writing the master list of units, which may be individual vtd's (+surrounds), whole counties, or corner county clusters\")\n",
    "for c in unitCounties:\n",
    "    unitCP.append(countyCP[c])\n",
    "    unitPop.append(countyPop[c])\n",
    "    unitGeom.append(   countyGeom[c] )\n",
    "    nbrUnitGeom.append(countyGeom[c] )\n",
    "    countyUnits.append(c)\n",
    "    allUnits.append(c+0.5)  #use non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nVTDneighbors = [0 for v in range(nVTDs)] #this loop -- just checking for surrounded VTDs\n",
    "lastVTDneighbor = [-999 for v in range(nVTDs)]\n",
    "\n",
    "nFragmentedVTDs,fragmentedVTDs, coastalFragmentedVTDs = 0, list(), list()  #a prev version treated coastal separately\n",
    "fragVTDgeom, parentVTDno, fragVTDpop = vtdGeom.to_list(), [v for v in range(nVTDs)], tractPop.to_list()  #these lists will expand to include vtd fragments \n",
    "origVTDgeom = vtdGeom.copy() #we create a parallel fragVTDgeom list which grabs the 1st fragment, then append fragments to the total list\n",
    "origVTDpop = tractPop.copy()\n",
    "VTDchildren = [[v] for v in range(nVTDs)]  #the list of all fragment numbers associated with the original VTD, including ones that get surrounded\n",
    "countyFragVTDset = [set(countyTractList[c]) for c in range(nCounties)]\n",
    "for v in populatedTractList:\n",
    "    c = countyNo[v]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        if vtdGeom[v].geom_type != dummyPoly.geom_type :  #a multipoly vtd-based unit\n",
    "            nFragmentedVTDs +=1\n",
    "            fragmentedVTDs.append(v)\n",
    "            geos, areas = [geo for geo in vtdGeom[v].geoms ], [geo.area for geo in vtdGeom[v].geoms]\n",
    "            for i, geo in enumerate(geos):\n",
    "                if i == 0:\n",
    "                    fragVTDgeom[v] = geo\n",
    "                    fragVTDpop[v] = tractPop[v] * areas[i] / np.sum(areas)  #overwrite, then distribute balance below\n",
    "                else:\n",
    "                    fNo = len(fragVTDgeom)\n",
    "                    fragVTDgeom.append(geo)\n",
    "                    fragVTDpop.append( tractPop[v] * areas[i] / np.sum(areas) )\n",
    "                    parentVTDno.append(v)\n",
    "                    countyFragVTDset[c].add(fNo )\n",
    "                    VTDchildren[v].append(fNo)\n",
    "                    nVTDneighbors.append(0)\n",
    "                    lastVTDneighbor.append(-999)\n",
    "                    \n",
    "print(\"I split up\",nFragmentedVTDs,\"fragmented VTDs. Now define unit neighbor lists and fuse geometries of surrounds.\")\n",
    "\n",
    "debugV = -7616\n",
    "for kk,V in enumerate(populatedTractList):\n",
    "    if kk%500 == 0:\n",
    "        print(\"looking for surrounds, now working on vtd\",V)\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties:\n",
    "        for v in VTDchildren[V]:\n",
    "            for vv in countyFragVTDset[c].difference({v}) :\n",
    "                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                    nVTDneighbors[v] +=1\n",
    "                    lastVTDneighbor[v] = vv\n",
    "                    if v == debugV:\n",
    "                        print(\"I just added neighbor\",vv,\"to magicV\",v)\n",
    "                #if nVTDneighbors[v] >= 4:  #Enough to have >=2 even after surrounds.  Will do full neighbor list later\n",
    "                #    break\n",
    "            if nVTDneighbors[v] < 4:  #OK if a vtd has only 1 intracounty neighbor IF it touches another county, it's not surrounded\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if fragVTDgeom[v].intersects(countyGeom[cc]):\n",
    "                        if cc not in unitCounties + allFusedCounties:\n",
    "                            for vv in countyFragVTDset[cc] :\n",
    "                                if fragVTDgeom[vv].intersects(fragVTDgeom[v]):\n",
    "                                    nVTDneighbors[v] +=1\n",
    "                                    lastVTDneighbor[v] = vv\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                print(\"WARNING. vtd frag\",v,\"in county\",c,\"intersected county\",cc,\"but had no intracounty neighbors\")\n",
    "                                plotPoly(fragVTDgeom[v],2)\n",
    "                                plotCenter(\"iso\",fragVTDgeom[v])\n",
    "                                plotPoly(countyGeom[cc])\n",
    "                        else:\n",
    "                            nVTDneighbors[v] +=1\n",
    "                            if nVTDneighbors[v] == 1:\n",
    "                                raise Exception(\"neighborless vtd fragment\",v,\"neighbors a unit or fused county\",cc)                                \n",
    "            if v == debugV:\n",
    "                print(v,\"has\",nVTDneighbors[v],\"neighbors.  its last is\",lastVTDneighbor[v])\n",
    "                \n",
    "for loop in range(3): #to catch surrounds of surrounds\n",
    "    for V in populatedTractList:\n",
    "        c = countyNo[V]\n",
    "        if c not in allFusedCounties and c not in unitCounties: \n",
    "            for v in VTDchildren[V]:\n",
    "                if nVTDneighbors[v] == 1:\n",
    "                    vv = lastVTDneighbor[v]\n",
    "                    if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "                        for sNo, s in enumerate(surroundedVTDs):\n",
    "                            if surrounders[sNo] == v:\n",
    "                                surrounders[sNo] = vv\n",
    "                    surroundedVTDs.append(v)\n",
    "                    surrounders.append(vv)\n",
    "                    nVTDneighbors[vv] -=1\n",
    "                    nVTDneighbors[v] -=1 #in case this surrounder becomes a later surroundee\n",
    "                    fragVTDpop[vv] += fragVTDpop[v]\n",
    "                    fragVTDpop[v] = 0\n",
    "                    if lastVTDneighbor[vv] == v:  #find another neighbor in case this surrounder is also a surroundee in loop 2\n",
    "                        for vvv in countyFragVTDset[c]:\n",
    "                            if vvv not in [v,vv]:\n",
    "                                if fragVTDgeom[vvv].intersects(fragVTDgeom[vv]):\n",
    "                                    lastVTDneighbor[vv] = vvv\n",
    "                    if lastVTDneighbor[vv] == v:\n",
    "                        print(\"WARNING.  We did not find another neighbor of surrounder\",vv,\"other than surroundee\",v)\n",
    "                    if loop > 0:\n",
    "                        print(\"On loop\",loop+1,\"for county\",c,\" we found that vtd frag\",v,\"now has only 1 neighbor\",vv)\n",
    "#NEW for MI -- allow manual entry of surrounders (needed rarely near a state border)\n",
    "#specialSurrounded = [3647, 5145 ]\n",
    "#specialSurrounder =  3646\n",
    "#print(\"special for MI, I believe that\", specialSurrounded,\"are surrounded by vtd (fragment)\",specialSurrounder,\". Here, let me show you\")\n",
    "#c = countyNo[parentVTDno[specialSurrounder]]\n",
    "#plotPoly(countyGeom[c])\n",
    "#for v in specialSurrounded:\n",
    "#    plotPoly(fragVTDgeom[v])\n",
    "#    plotCenter(v,fragVTDgeom[v])\n",
    "#plotPoly(fragVTDgeom[specialSurrounder],0.2)\n",
    "#plotCenter(specialSurrounder, fragVTDgeom[specialSurrounder], 8)\n",
    "#plt.show()\n",
    "#shouldIcombine = int(input(\"enter 1 to apply the surrounding operation\"))\n",
    "#if shouldIcombine == 1:\n",
    "#    for v in specialSurrounded:\n",
    "#        vv = specialSurrounder\n",
    "#        if v in surrounders:  #transferring surrounded of surrounds to master surrounder\n",
    "#            for sNo, s in enumerate(surroundedVTDs):\n",
    "#                if surrounders[sNo] == v:\n",
    "#                    surrounders[sNo] = vv\n",
    "#        surroundedVTDs.append(v)\n",
    "#        surrounders.append(vv)\n",
    "#        nVTDneighbors[vv] -=1\n",
    "#        nVTDneighbors[v] = 0 #we are capturing all surroundees (some of whom may touch other surroundees)\n",
    "#        fragVTDpop[vv] += fragVTDpop[v]\n",
    "#        fragVTDpop[v] = 0\n",
    "\n",
    "\n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] >1:\n",
    "                unitCP.append(fragVTDgeom[v].centroid)\n",
    "                unitGeom.append(fragVTDgeom[v])\n",
    "                unitPop.append(fragVTDpop[v])   #for now, ratio pop by area, not block decomposition\n",
    "                vtdUnits.append(v)   #if a border unit, we'll catch in below big loop, after checking for surround\n",
    "                allUnits.append(v)\n",
    "#for V in populatedTractList:\n",
    "#    c = countyNo[V]\n",
    "#    if c not in allFusedCounties and c not in unitCounties:  \n",
    "#        for v in VTDchildren[V]: \n",
    "for V in populatedTractList:\n",
    "    c = countyNo[V]\n",
    "    if c not in allFusedCounties and c not in unitCounties: \n",
    "        for v in VTDchildren[V]:\n",
    "            if nVTDneighbors[v] == 1:  #a surrounded VTD, transfer its pop to surrounder unit.  Don't bother with shifting centerpoints\n",
    "                print(\"somehow we missed 1-neighbor vtd frag\",v,\" with last vtd frag nbr\",lastVTDneighbor[v])\n",
    "            if nVTDneighbors[v] == 0 and v not in surroundedVTDs:\n",
    "                print(\"WARNING. unsurrounded vtd\",v,\"had no found neighbors\")\n",
    "\n",
    "for i, L in enumerate(CCBlist):\n",
    "    unitCP.append( CCBcp[i] )\n",
    "    unitPop.append(CCBpop[i])\n",
    "    unitGeom.append(   CCBgeom[i])\n",
    "    nbrUnitGeom.append(CCBgeom[i])\n",
    "    allUnits.append(i+0.25)  #use alt non-integers to avoid vtd and county and cluster confusion\n",
    "\n",
    "nUnits = len(allUnits)\n",
    "print(\"After surround checks, we appear to have\",nUnits,\"building blocks defined. We captured\",len(surroundedVTDs),\"surrounded VTDs\")\n",
    "\n",
    "unitNbrs = [list() for u in range(nUnits)]\n",
    "countyUnitList = [list() for c in range(nCounties)]\n",
    "for c in uncutCountyList:\n",
    "    for v in countyFragVTDset[c]:\n",
    "        if v in allUnits:\n",
    "            countyUnitList[c].append(allUnits.index(v))\n",
    "\n",
    "sketchyList = list()\n",
    "for c in uncutCountyList:\n",
    "    if c%20 == 0:\n",
    "        print(\"working on unit neighbor lists for county\",c)\n",
    "    if c not in allFusedCounties:  #see a separate loop below for cluster-cluster neighbors\n",
    "        if c in unitCounties:    \n",
    "            u = allUnits.index(c+0.5)\n",
    "            for cc in neighborCountyList[c]:\n",
    "                if cc not in allFusedCounties:\n",
    "                    if cc in unitCounties:\n",
    "                        unitNbrs[u].append(allUnits.index(cc+0.5))  #we'll catch the complement in the cc county's loop\n",
    "                    else:\n",
    "                        for uu in countyUnitList[cc] :\n",
    "                            if countyGeom[c].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu)\n",
    "                                unitNbrs[uu].append(u)\n",
    "            for i,geo in enumerate(CCBgeom):\n",
    "                if geo.intersects(countyGeom[c]):\n",
    "                    unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                    unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "        else:  #non-unit county      \n",
    "            for u in countyUnitList[c] :\n",
    "                for uu in list( set(countyUnitList[c]).difference({u}) ) :\n",
    "                    if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                        unitNbrs[u].append(uu )  #will catch complement later in this county's loop\n",
    "                for cc in neighborCountyList[c]:\n",
    "                    if cc not in allFusedCounties and cc not in unitCounties: #see an above block for handling unitCounties\n",
    "                        for uu in countyUnitList[cc]:\n",
    "                            if unitGeom[u].intersects(unitGeom[uu]):\n",
    "                                unitNbrs[u].append(uu )\n",
    "\n",
    "            for u in countyUnitList[c] :\n",
    "                for i,geo in enumerate(CCBgeom):\n",
    "                    if geo.intersects(unitGeom[u]):\n",
    "                        unitNbrs[u].append(allUnits.index(i+0.25) )\n",
    "                        unitNbrs[allUnits.index(i+0.25) ].append(u)\n",
    "                if len(unitNbrs[u]) == 0:\n",
    "                    print(\"ERROR - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has no neighbors\")\n",
    "                if len(unitNbrs[u]) == 1:  #after fragmentation, this unit appears surrounded.  Next block to confirm it has non-intracounty neighbors                       \n",
    "                    print(\"WARNING - unit\",u,\" = vtd\",allUnits[u],\"in county\", c,\"has only 1 neighbor=\",unitNbrs[u],\". Optional triage in next block\")\n",
    "                    sketchyList.append([u,unitNbrs[u][0] ] )\n",
    "\n",
    "CCBunits = CCBlist.copy()                        \n",
    "for i, geo in enumerate(CCBgeom):  #this loop: only cluster-cluster intersections.  Cluster-vtd and cluster-county neighbors already found above.\n",
    "    for ii in range(i+1,len(CCBgeom) ) :\n",
    "        if geo.intersects(CCBgeom[ii]):\n",
    "            unitNbrs[allUnits.index(i+0.25) ].append(allUnits.index(ii+0.25) ) #all CCB-county, CCB-vtd intersxns already covered\n",
    "            unitNbrs[allUnits.index(ii+0.25)].append(allUnits.index(i+0.25) )\n",
    "print(\"All done creating unit lists\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "94741893-6835-45ac-9793-64cbaf4823b2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sketchy unit 717 has neighbor list [667, 3]\n",
      "sketchy unit 718 has neighbor list [667, 3]\n",
      "sketchy unit 18 has neighbor list [16, 2]\n",
      "sketchy unit 2437 has neighbor list [2419, 12]\n",
      "sketchy unit 959 has neighbor list [927, 13]\n",
      "sketchy unit 933 has neighbor list [855, 11]\n"
     ]
    }
   ],
   "source": [
    "for L in sketchyList:  #hope that some of these flagged units picked up a \n",
    "    print(\"sketchy unit\",L[0], \"has neighbor list\",unitNbrs[L[0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "cb4277b4-d6ef-4c8c-aa23-6fde227379ff",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "id": "e79873ab-0b8e-48a9-b4b0-05b3135b9cc3",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "8378940d-4387-4188-8ae1-a62010500ecb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now build the border topology\n",
      "counties and clusters done, now working on (frag) vtd-based units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"Now build the border topology\")\n",
    "borderUnits, borderType = list(), list()\n",
    "for c in borderCounties:\n",
    "    if c in unitCounties:\n",
    "        borderUnits.append(allUnits.index(c+0.5))\n",
    "        borderType.append(\"county\")\n",
    "for i,L in enumerate(CCBlist):\n",
    "    if CCBgeom[i].intersects(MAPexterior):  #should always be the case\n",
    "        borderUnits.append(allUnits.index(i+0.25))\n",
    "        borderType.append(\"cluster\")\n",
    "print(\"counties and clusters done, now working on (frag) vtd-based units\")\n",
    "for c in borderCounties:\n",
    "    if c not in unitCounties + allFusedCounties:\n",
    "        for u in countyUnitList[c]:\n",
    "            if unitGeom[u].intersects(MAPexterior):\n",
    "                borderUnits.append(u)\n",
    "                borderType.append(\"vtd\")                \n",
    "    \n",
    "for i,b in enumerate(borderUnits):\n",
    "    plotPoly(unitGeom[b])\n",
    "    if borderType[i] == \"cluster\":\n",
    "        j = int(allUnits[b])\n",
    "        for c in CCBlist[j]:\n",
    "            plotPoly(countyGeom[c],0.2)\n",
    "            plotCenter(\"fused\",countyGeom[c], 6)\n",
    "for c in unitCounties:\n",
    "    plotPoly(countyGeom[c],0.4)\n",
    "    plotCenter(\"unit\",countyGeom[c],8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "937d923d-9e95-45e9-9aef-77cb4377781d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking that the list of borderUnits is contiguous all around\n",
      "number of border units = 72\n"
     ]
    }
   ],
   "source": [
    "print(\"checking that the list of borderUnits is contiguous all around\")\n",
    "print(\"number of border units =\",len(borderUnits))\n",
    "for u in borderUnits:\n",
    "    isUnbroken, smallPieceList = isContiguous(list(set(borderUnits).difference({u})),unitNbrs)\n",
    "    if not isUnbroken:\n",
    "        print(\"border is discontig if we skip\",u)\n",
    "        for uu in smallPieceList:\n",
    "            plotPoly(unitGeom[uu],0.5)\n",
    "            plotCenter(\"n\"+str(uu),unitGeom[uu])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        plotPoly(unitGeom[u])\n",
    "        plt.show()\n",
    "borderSet = set(borderUnits)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "93603f77-77fa-4453-b54b-5ea07fcb6721",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here, we identify 'border' units that aren't needed to define the map border\n",
      "Bueno! no 'border units' that could be eliminated from the border set\n"
     ]
    }
   ],
   "source": [
    "print(\"here, we identify 'border' units that aren't needed to define the map border\")\n",
    "canBeRemoved, powerNeighbors = set(), set()\n",
    "for u in borderUnits:\n",
    "    uNeighbors = list(borderSet.intersection(set(unitNbrs[u])) )\n",
    "    if len(uNeighbors) < 2:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(u,unitGeom[u])\n",
    "        uu = uNeighbors[0]\n",
    "        otherBorderNeighbors = set(unitNbrs[uu]).intersection(borderSet).difference({u})\n",
    "        if len(otherBorderNeighbors) > 1:  #this neighbor of our 1-border-neighbor border unit makes a border chain without the problem border unit\n",
    "            canBeRemoved.add(u)\n",
    "            powerNeighbors.add(uu)\n",
    "        plotCenter(uu,unitGeom[uu],6)\n",
    "        plotPoly(unitGeom[uu],0.5)\n",
    "        for uuu in set(unitNbrs[uu]).intersection(borderSet).difference({u}):\n",
    "            plotPoly(unitGeom[uuu])\n",
    "            plotCenter(str(uuu)+\"=N of\"+str(uu),unitGeom[uuu])\n",
    "        for uuu in set(unitNbrs[u]).difference(borderSet):\n",
    "                plotCenter(uuu+0.1,unitGeom[uuu],6)\n",
    "                plotPoly(unitGeom[uuu],0.1)\n",
    "        c = countyNo[allUnits[u]]\n",
    "        #plotPoly(countyGeom[c] )\n",
    "        #plotCenter(c, countyGeom[c])\n",
    "        plt.show()\n",
    "if len(canBeRemoved) == 0:\n",
    "    print(\"Bueno! no 'border units' that could be eliminated from the border set\")\n",
    "else:\n",
    "    print(canBeRemoved,\"is the list of 1-neighbor 'border' units that can be eliminated from the border set\")\n",
    "    print(\"... as they are enveloped on the border; the enveloping border unit has two other map-border neighbors\")\n",
    "    yesRemove = input(\"enter 1 to remove these from the list of border units\")\n",
    "    if int(yesRemove) == 1:\n",
    "        canRemove = True\n",
    "        for uu in powerNeighbors:\n",
    "            testSet = (borderSet.difference(canBeRemoved)).difference({uu})\n",
    "            if not isContiguous(list(testSet),unitNbrs):\n",
    "                canRemove = False\n",
    "                print(\"We can't complete the border if unit\",uu,\"is not included in the ring\")\n",
    "        if canRemove:\n",
    "            borderSet = borderSet.difference(canBeRemoved)\n",
    "            borderList = list(borderSet)\n",
    "            borderUnits = list(borderSet)\n",
    "            print(\"Success! we removed\",canBeRemoved,\"from the list of borderUnits\")\n",
    "    else:\n",
    "        print(\"Fine, be that way.  Sheesh, I will keep them.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "b13c68e3-33ed-48b3-acca-78012ce0bf61",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here is the final border set\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "print(\"here is the final border set\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "173bb175-312b-4d08-a5b5-80a1d5d70416",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True\n"
     ]
    }
   ],
   "source": [
    "print(isContiguous(borderUnits,unitNbrs)[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "fc1ae6e1-ef52-412b-a966-e9739071af8f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "For safekeeping, write the unit topology to a file\n"
     ]
    }
   ],
   "source": [
    "date_ = \"06Apr24\"\n",
    "print(\"For safekeeping, write the unit topology to a file\")  \n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        #for i,uu in enumerate(surrounders):  #no longer tracked\n",
    "         #   if u == uu:\n",
    "         #       unitVTDlist[u].append(surroundedVTDs[i])\n",
    "                \n",
    "unitNo = [u for u in range(nUnits)]\n",
    "unitCPx, unitCPy = [unitCP[u].x for u in range(nUnits)], [unitCP[u].y for u in range(nUnits)]\n",
    "onBorder = [0 for u in range(nUnits)]\n",
    "for u in borderUnits:\n",
    "    onBorder[u] = 1\n",
    "nbrDF = pd.DataFrame( {\"unitNo\":unitNo,\"centroid x\":unitCPx,\"centroid y\":unitCPy,\"unitPop\":unitPop,\"onBorder\":onBorder,\n",
    "                       \"neighborList\":unitNbrs, \"unitVTDlist\":unitVTDlist, \"unitParentVTDno\": unitParentVTDno, \"allUnits\":allUnits} )\n",
    "outname = STATE+\"unitTopologies_\"+date_+\".csv\" \n",
    "outpath = \"state_map_files/\"+outname\n",
    "nbrDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d4baaea4-7af4-4407-aeb3-f4291d335f89",
   "metadata": {},
   "outputs": [],
   "source": [
    "vtdGeom = tractGeom.copy()  #optional reset if we need to rerun the below clipPoly routine with alternate clipPolys"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "abdd07e7-f9be-480a-9d3d-b3948eeaaa2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "toSquishCountiesList = list()   #default; if we did not have any clipPoly's to move in\n",
    "nClips = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "4d5fdc3c-6126-4fa8-b484-1d0052c70aed",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for some states like FL, MD, MN we move in partial counties via clipPoly's before running option 2\n",
      "adding code here to 'push in' state panhandles ...\n",
      "performing squish no 1 for state MN\n",
      "clipPoly 0 intersects [8, 15, 35, 37, 68] counties and a total of 170 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 1 out of 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "performing squish no 2 for state MN\n",
      "clipPoly 1 intersects [19, 22, 24, 27, 49, 54, 78, 84] counties and a total of 279 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 2 out of 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "performing squish no 3 for state MN\n",
      "clipPoly 2 intersects [5, 77] counties and a total of 11 units\n",
      "Here is the original cutLine and an alternate based on cut shapes\n"
     ]
    },
    {
     "data": {
      "image/png": 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qqs1Kj0QWYo+JiJTA8NIWNJr/dV0MgYAxV9l5rEj/IHe8M3kgfjqcj+c2HYANXHao3bm8x5RTwB4TEbUuhpe2ptXxyMtlbg31weK7+2L97pN466cspcchGWp7TA52WsSsYo+JiFoXwwtZhfsigjDv9h7475Yj+Dg5R+lxSIYOrnokxkXhUmklZiQms8dERK2G4YWsxt9uC8GkwZ2wcGMGfjp8VulxSIbaHtOhvCL2mIio1TC8kNWQJAmLxoXhtlAfzFm3F2k5l5QeiWRgj4mIWhvDS1urqgC09kpPYbW0GgnLJg5A7wAD4hKScexcsdIjkQz1e0zL2GMiohbG8NLWis8Arn5KT2HVHOy0WBkTAQ8nO8SsSsK5IpPSI5EMtT2mV7ccwUfJJ5Ueh4hsCMNLW6h/2Ly6EtDaKTeLSrg72SMxLgqmSjOmJySh2FSl9Egkw99uC8HkwZ3w9Mb97DERUYtheGkLxtMt887U7UyghxMSpkfhj/OleHhtCiqqWP5UG0mS8CJ7TETUwhhe2kK1CbBzVHoKVeodYMDyqYOw69gF/P2zdJY/VYg9JiJqaQwvZPWGhHjjv/f1x+d7T+HlzZlKj0MyXN5jyi8qV3okIlIxhpc2ITXsvZDFxvYLwDNjeuG9n7OR8PtxpcchGWp7TBVVZsQlJLPHRESyMby0BZ0eqOIZM9frwVu6YeYtXfHC1wfxbUae0uOQDOwxEVFLYHhpC1o9UPXnYXJJUnYWlVt4Ry/8JTwAcz9Kw+5jF5Qeh2To5c8eExFdH4aXtqDTA9V/vlEdn6ivi0Yj4ZV7wxHR2QMPrt6DzDNFSo9EMrDHRETXg+GlLejqHXmh66bXabF86iAEejghJj4Jpy+VKT0SycAeExHJxfDSFjQ6wMxyYktydbBD4vRIaDUSYlclobC0UumRSIb6PaZv0tljIqLmYXhpCxLPNmoNPgYHJMZFIb/IhJlr9qC8slrpkUiG2h7TEx+lYRd7TETUDAwvbaW2qMvCbosK8XHBypgI7Mu5hCc+SkO1mSFRbep6TF08MJM9JiJqBoaXNicBZp4e2pIGdfbEW5MG4vsDZ/DiVwd49ooKscdERJZgeGlrOgeWd1vB7b198a+/9kXizj/w7s/ZSo9DMtTvMcXEs8dERFfG8NLWtPb/O22aWtSkwZ3wWHR3LN2cic9ScpUeh2TwMThg9YwonCs2YeZq9piIqGkML21OsPfSip4Y0R33RwRhwWfp+PnIOaXHIRmCO7hgZUwk9uWyx0RETWN4aWtCAGB4aS2SJOGl8WEY2qMDHl6bgozcQqVHIhkGdfZgj4mIrojhpc3xyEtr02k1eGvSAHT3dcX0hCT8caFE6ZFIBvaYiOhKGF7aGo+8tAknex3iYyLg6mCHmPgknC/mG2OqEXtMRNSU6wovS5YsgSRJmDt3bt3nhg8fDkmSGmyzZ8++6n4uv3/t9sorr1zPeFaKR17aipeLHqvjolBsqsaMhGSUVvAqx2r0xIjueCCypse0PTNf6XGIyArIDi/JyclYvnw5wsPDG902c+ZM5OXl1W1Lly696r7q3zcvLw/x8fGQJAkTJkyQO5714pGXNhXk6YSE6ZHIyi/GnHWpqKzmNXbURpIk/OuvNT2mR9alssdERPLCS3FxMSZPnowVK1bAw8Oj0e1OTk7w8/Or2wwGw1X3V/++fn5++PLLL3HrrbeiW7ducsazcjzy0tbCOrrhvamD8OvR8/jHxgyWP1WIPSYiqk9WeJkzZw7GjBmDESNGNHn7unXr4O3tjbCwMCxcuBClpaXN3vfZs2fxzTffYMaMGVe8j8lkgtFobLCpRnUFoLFTeop255buHfDKveH4eE8uXt1yROlxSAb2mIiols7SB2zYsAGpqalITk5u8vZJkyahc+fOCAgIQHp6OhYsWIDMzEx8/vnnzdp/YmIiXF1dcffdd1/xPosXL8YLL7xg6ejWwVwNaC3+Y6cWMH5AIM4aTVjy3WH4Ghww5YbOSo9EFqrtMY1/ZwdmJCRj/cwb4Kzn/yei9kYSFhxDz8nJQUREBLZs2VLXdRk+fDj69++P119/vcnH/PTTT4iOjkZWVhaCg4Ov+TVCQ0Nx++23Y9myZVe8j8lkgsn0v5+6jEYjgoKCUFhYeM2XqBRRVQGU5ANugcCFbMDr2n8O1DqEEHjhq4NYvfME3p0yCKP6+Ck9Esmw/1Qh7l++E5FdPbFiWgTstDxxkkiNjEYj3NzcLP7+bdH/+JSUFOTn52PgwIHQ6XTQ6XT4+eef8eabb0Kn06G6uvGlvAcPHgwAyMrKuub+f/31V2RmZuLBBx+86v30ej0MBkODzapVFAN2TkpPQagpfz53V2/cEeaPxz7ciz0nCpQeiWSo7TH9dvQ8nv6cPSai9sai8BIdHY2MjAykpaXVbREREZg8eTLS0tKg1WobPSYtLQ0A4O/vf839r1y5EoMGDUK/fv0sGcv6VZQA9i5KT0F/0mgk/Pe+fugf5I4ZiXuQlV+k9EgkQ22P6ZMU9piI2huLwourqyvCwsIabM7OzvDy8kJYWBiys7OxaNEipKSk4MSJE9i0aROmTZuGoUOHNjilOjQ0FBs3bmywb6PRiE8++eSaR11UqboC0NkrPQXV42CnxfvTIuBncEBMfDLOGvlO32o0fkAg/n5HKJb9lIW1u/5QehwiaiMt+kKxvb09tm7dipEjRyI0NBTz5s3DhAkT8NVXXzW4X2ZmJgoLG16rYcOGDRBCYOLEiS05EtEVuTnaISEuEmYhEBOfBGN5pdIjkQwPDe2G2CFd8NyX+/H9gTNKj0NEbcCiwq61klv4aTP1S7os7FqdI2eLcM+7O9AnwA0JcZHQ6xq//EnWzWwWePTDvdh66CzWPTgYEV08lR6JiJqhTQq7RLaoh68rPoiJRMrJi5j38T6YzarP8+0Oe0xE7QvDCxGAqK6eePOB/vgmIw8vfXtI6XFIBvaYiNoPhheiP40O88cLY/tg5W/HseKXY0qPQzKwx0TUPjC8ENUz7cYueGR4MF769hC+TDul9Dgkg7+bIxLjonD6Uhlmrd4DU1Xj608RkboxvBBdZv6onpgwMBBPfbIPv2edV3ockqGHrytWxkYi9eQlPMkeE5HNYXhpC3wXaVWRJAlLJvTFjcHeeGhNCg6cLrz2g8jqRHap6TF9yx4Tkc1heGkL6j8bvd2x02rw7uSB6OrtjNhVycgpaP47o5P1YI+JyDYxvBBdgbNeh/jYSDjZaxGzKgkXSyqUHolkYI+JyPYwvBBdRQdXPRKnR6GwtBJxickoq2D5U43YYyKyLbzCbls4fxRwC6r5+EIWIF0hMzarG3ON+1xzHy31eHHZ7y97fP1/Vs3t/Fx+v8v/aVp6e3PmaObth84U4/ENezGosycWjesDnZY9JrWprBZ4+vMM7D9diDcm9kcPH1elR6LWIgRg5wQYrv2GwKQsud+/GV7agqmoZruaZv01NOM+trofK7Dz2AU8/fl+3NnXH0+N7NH8Hnbtn8HVwlNzdiZ3P5ffVv/3rXFbS3+Npu4r5zYApRXVmPtRGs4Vm/D2pEEIcNPL2k8Dcm+zREvtpz0QAvAOqXnOLTkPeHZVeiK6Crnfv3WtOBPV0rvWbKRqN3p2wyPww/xP02HfoRqPj+iu9EhkIScAL83ojHve24EpG/Px2ewh8HDmO77blII/i9l6V6A4X9lZqNWw80JkgXsjgvDUyB54besRbEg6qfQ4JAN7TDaOR6jaBYYXIgvNuTUEU2/ojH98sR8/Hjqr9DgkQxdvZ8THRuJwXhEe/TAVVdVmpUciIgswvBBZSJIk/HNsH4zo5YM561Ox9+RFpUciGfoFueOdKQOxLfMcnv1yP2yg/kfUbjC8EMmg1Uh444EBCAtwQ1xCMo6dK1Z6JJLh1p4+WHJ3X3yYlIM3f8xSehwiaiaGFyKZHOy0+CAmAl4uekyLT0J+UbnSI5EM7DERqQ/DC9F1cHeyR2JcFCqrzZi+KhlF5ZVKj0QysMdko/i+cjaL4YXoOnV0d0RiXBROXijFw2tTUVHF8qfaXN5jSmWPiciqMbwQtYBQPwPenxaBpOMF+L9P98FsZvlTber3mGYkJCObPSb1YwnbZjG8ELWQG4O98Or9/fBF2mm8/P1hpcchGer3mGLYYyKyWgwvRC3orvAAPHtXbyz/+RhW/X5c6XFIBvaYiKwfwwtRC5txc1fMGtoNL359EF+nn1Z6HJKBPSaV48tFNo/hhagV/H10KMb1C8CTH+3DzuwLSo9DMrDHpFLO3kAp/8/ZOoYXolag0UhYek8/RHX1xKw1e3D4jFHpkUiG2h7Tl/tO4+XN7DGpgqQFzH++XxVPlbZZDC9ErcRep8G7UwYiyMMJsfHJOH2pTOmRSIa7wgPw7JjeWP7LMcT/xh6T1RNmhpZ2gOGFqBW5OtghYXokdFoJMfFJuFRaofRIJEPczV3x0NBuWPQNe0xE1oDhhaiV+RgckBgXhfPFJsxcvQflldVKj0QyLGCPSR0kTc3RF4DFXRvG8ELUBoI7uGBlbCQyThXi8Q17Uc3yp+qwx6QSmnqdF7JZDC9EbWRgJw+8NXEgthw8i39uOgDBnwpVp36PKSY+CafYY7I+khYQDC+2juGFqA2N6O2Ll8b3xZpdf+Cd7dlKj0MyuDrYISEuEnZaDXtM1kij45GXdoDhhaiNTYzqhMeju+OV7zPxaUqu0uOQDD6uNT2mC+wxWR+NBgCPato6hhciBcwd0R0To4Kw4LN0bM/MV3ockoE9JiLlMLwQKUCSJCwaF4Zbe3bAI+tSsS/nktIjkQzsMREpg+GFSCE6rQbLJg5ETz9XxCUk448LJUqPRDKM6O2Lf7PHRNSmGF6IFORor8XKmEi4OdphWnwSzheblB6JZHggqhPmjqjpMX2yJ0fpcaj2CBivtGuzGF6IFObpbI/EuCiUVlQjLiEZJaYqpUciGR6Prukx/f3zDPaYrImZ7whuixheiKxAkKcTVsVG4ti5EjyyLhWV1XzCVRv2mKyQ1h4wVyo9BbUChhciKxHW0Q3vTRmEHdnn8ffPMlj+VKHLe0wnzrPHpCitPVDN8GKLGF6IrMjN3b3xn3v74bPUXPz3hyNKj0My1O8xxaxij0lRGh1QzYsI2iKGFyIrM65/Rzx9Zyje2paFNbv+UHockoE9JishRM0bNZLN4d8qkRWaeUs3TL+pC577cj827z+j9DgkQ5CnExKms8ekKHNlzUtHZHMYXoiskCRJeHZMb9zZ1x+PbdiL5BMFSo9EMvQJYI9JUdUVgNZO6SmoFTC8EFkpjUbCq/f1w8BO7piRkIyjZ4uUHolkqN9j+s8PmUqP076Yq2p6L2RzGF6IrJhep8X70yIQ4O6ImPgknCksV3okkqG2x/T2tmys2XlC6XHaF16oziYxvBBZOYODHRKmRwEAYlclobCMp36q0cxbuiHupq54btMB9piIrhPDC5EK+Lk5IDEuCnmF5XhozR6YqqqVHoksJEkSnhnTiz2m1sZeUbvA8EKkEt19XfFBTAT2nryEJz/eB7OZT9Jqwx5TG6gqB3QOSk9BrYzhhUhFIrt44o0HBuC7jDws+uYgz15Roct7THmFZUqPZFsqywA7x5qP+f/DZjG8EKnM6DA/vDAuDKt+P4EVvx5TehySobbHJEkSYuOT2WNqSfXDC8u6NovhhUiFpt7QGX+7NQT//vYwvth7SulxSIaaHlMkzhjLMWv1HpRXssfUIuq/bMQjLzbrusLLkiVLIEkS5s6dW/e54cOHQ5KkBtvs2bOvua9Dhw5h7NixcHNzg7OzMyIjI3Hy5MnrGY/Ips0b2QP3DArE/E/34bej55Ueh2QI8XHFypgIpOVcwjz2mFoOj7jYPNnhJTk5GcuXL0d4eHij22bOnIm8vLy6benSpVfdV3Z2Nm6++WaEhoZi+/btSE9Px7PPPgsHB5auiK5EkiQsvrsvbgrxxkNr9mD/qUKlRyIZImp7TPvZYyJqLlnhpbi4GJMnT8aKFSvg4eHR6HYnJyf4+fnVbQaD4ar7+8c//oE777wTS5cuxYABAxAcHIyxY8fCx8dHznhE7YadVoO3Jw1EsI8LYlclI6egVOmRSIb6Pab3f2GPiehaZIWXOXPmYMyYMRgxYkSTt69btw7e3t4ICwvDwoULUVp65SdUs9mMb775Bj169MCoUaPg4+ODwYMH44svvrjiY0wmE4xGY4ONqL1y1usQHxsJF70WMfFJKCipUHokkqG2x7T4u8PYuDdX6XGIrJrF4WXDhg1ITU3F4sWLm7x90qRJWLt2LbZt24aFCxdizZo1mDJlyhX3l5+fj+LiYixZsgSjR4/GDz/8gPHjx+Puu+/Gzz//3ORjFi9eDDc3t7otKCjI0mUQ2RRvFz0S46JQWFaJGYnJKKtg+VON5o3sgXsHBWL+J+n49eg5pcdRp/ovuwm+k7etkoQFL7Dm5OQgIiICW7Zsqeu6DB8+HP3798frr7/e5GN++uknREdHIysrC8HBwY1uP336NDp27IiJEydi/fr1dZ8fO3YsnJ2d8eGHHzZ6jMlkgslkqvu90WhEUFAQCgsLr/kSFZEtS8+9hAfe34Ubu3lh+dRB0Gl5QqHaVFabMXP1HiQfL8BHD92IsI5uSo+kLheyAa8/v9cUHAM8uyk7D12V0WiEm5ubxd+/LXpmS0lJQX5+PgYOHAidTgedToeff/4Zb775JnQ6HaqrG/+0N3jwYABAVlZWk/v09vaGTqdD7969G3y+V69eVzzbSK/Xw2AwNNiICAgPdMc7kwfi5yPn8MwX+1n+VCH2mIiuzaLwEh0djYyMDKSlpdVtERERmDx5MtLS0qDVahs9Ji0tDQDg7+/f5D7t7e0RGRmJzMyGbxV/5MgRdO7c2ZLxiAjA8J4+WDIhHBuSc/D61qNKj0My1O8xTWOPST6Gd5uls+TOrq6uCAsLa/A5Z2dneHl5ISwsDNnZ2Vi/fj3uvPNOeHl5IT09HU888QSGDh3a4JTq0NBQLF68GOPHjwcAzJ8/H/fffz+GDh2KW2+9FZs3b8ZXX32F7du3X/8KidqhewYF4qyxHK98nwk/NwdMjOqk9Ehkodoe04R3dyAuIRnrZw6Gk71FT9lENqtFXxC3t7fH1q1bMXLkSISGhmLevHmYMGECvvrqqwb3y8zMRGHh/65JMX78eLz33ntYunQp+vbtiw8++ACfffYZbr755pYcj6hdeWR4MKbd2Bn/2JiBrQfPKj0OydDZyxnxsZE4crYIj67fi6pqFlCJAAsLu9ZKbuGHyNZVmwXmrEvF9iP5WD/zBgzs1Pi6TGT9tmfm48HEPbhnUCAW390XEq8ge2X1C7v1Pyar1CaFXSJSF61GwusP9Effjm6YkZCM7HPFSo9EMrDHRNQQX0AlsnEOdlp8MC0S97y3A9NWJmHjI0PgY+Bbb6hN/R6Tr8EBkwazx3RNlaU1p0tbqvYFCSWPcEkawK0ToOExhqbwT4WoHXBzskNiXBSqzQIxq5JRVF6p9EgkQ22P6ZkvMrCFPaam2TnWvFx0IRuwc6oJIpZuteQ89nq36irAwR0wBAJ5exX7Y7R27LwQtSOHzxhx73s7ER7ohlWxUbDX8ecXtak2C/xtfSq2ZeZj3YM3YFBn9phsTm1Xpx10dth5IaJrCvUz4P2pEUg+fhHzP90Hs1n1P7u0O1qNhNfu74/wju6Ykcgek02zdwZMRUpPYZUYXojamRuDvfDa/f2xad9pLNl8WOlxSAYHOy1WTItABxc9pq1MQr6xXOmRqDU4+wAlfI+rpjC8ELVDY8L98dxdvfH+L8ew8rfjSo9DMrDH1A5oNLxK8BUwvBC1U9Nv6oqHhnXDoq8P4qt9p5Ueh2QIcHdEYlwUci+WYvbaFFRU8SJ21D4wvBC1YwtGhWL8gI6Y9/E+7Mg+r/Q4JENPP1esmFbTY3rqE/aYqH1geCFqxzQaCS9PCMfgbp54aHUKDuUZlR6JZLihW02P6at09piofWB4IWrn7HUavDtlEDp5OSF2VRJOXSpTeiSSgT0mak8YXogILnodVk2PhL1Og5j4JFwqrVB6JJKBPSZqLxheiAgA4OPqgMTpUSgoqcCMxD0or6xWeiSSgT0mag8YXoioTrcOLlgZE4EDpwvx2Id7Uc3yp+pc3mM6eJo9JrI9DC9E1MCATh54e9JA/Hg4H89v2g8beAeRdufyHlPuxVKlRyJqUQwvRNRIdC9fvPTXMKzddRJvb8tSehySobbHpLfTIHZVMntMZFMYXoioSQ9EdcITI3rgPz8cwcd7cpQeh2Rgj4lsFcMLEV3RY9EhmBjVCQs/z8C2w/lKj0My1PaYDp42ssdENoPhhYiuSJIkLBrXB7f29MEj61KxL+eS0iORDAM6eeDtyQPw4+F8PPcle0ykfgwvRHRVOq0GyyYOQC9/V8QlJOPE+RKlRyIZbgv1xb/Hh2HdbvaYSP0YXojomhzttVgZEwk3JztMi0/CuSKT0iORDPdHssdEtoHhhYiaxcPZHonTo1BWWY24hGSUmKqUHolkYI+JbAHDCxE1W5CnExKmR+L4+RI8vC4VldVmpUciC13eY0pjj4lUiOGFiCzSJ8ANy6cOws7s81jwWTrLnyp0eY/pOHtMpDIML0RksZtCvPGfe/vh89RTeOX7TKXHIRlqe0zuTnaIYY+JVIbhhYhkGde/I/5xZy+8sz0biTtOKD0OycAeE6kVwwsRyTZzaDfMuLkr/vnVAXyXkaf0OCQDe0xWTpKUnsAqMbwQ0XX5x529cFd4AB7/KA1JxwuUHodk6BPghvfZY7IeDCzXxPBCRNdFo5Hwn3vDMaiTBx5MTMaRs0VKj0QyDAnxxn/v64/PU09hKXtMypI0QHVlzccMkk1ieCGi66bXabF82iAEuDsiJj4JeYVlSo9EMoztF4BnxvTCu+wxKcvBDSj98yimEAwwTWB4IaIWYXCwQ2JcFDSShNj4ZBSWVSo9Esnw4C3sMSmu7CLg6lvzsSTxZaQmMLwQUYvxNTggMS4SZ4zlmLl6D8orq5UeiWRgj4msHcMLEbWoEB9XxMdGYF/OJTz5cRqqzTzkrTbsMZG1Y3ghohY3qLMn3pw4AJv3n8Girw/y7BUVurzHdPoSe0xkPRheiKhVjOrjhxfHhSFhxwks/+WY0uOQDA16TKuS2GMiq8HwQkStZsoNnfHobSFY8t1hfJ6aq/Q4JENtj+ms0cQeU1vi0cqrYngholb15O09cF9EIP7v03T8cuSc0uOQDOwxtTFJA4g/r3TMM42axPBCRK1KkiS8NL4vbunujYfXpmD/qUKlRyIZBnX2xDL2mNpG/fBCTWJ4IaJWZ6fV4O3JAxHi44LYVUk4eaFU6ZFIhpF9/LDorzU9pvd+Zo+p1UhahpdrYHghojbhZK9DfGwkXPQ6xKxKwoVik9IjkQyTB3fGY7eF4OXN7DG1Gh55uSaGFyJqM14ueqyOG4yi8krEJe5BaUWV0iORDE+wx9S6GF6uieGFiNpUJy8nrIqNQtbZIvxt/V5UVfNJWm3YY2pl9k7ApZM1H+sNwKUcZeexQgwvRNTm+ga64d0pg/DLkXN4emMGy58qVNdj8nVlj6ml6V0BrX3Nx87eQFW5svNYIYYXIlLE0B4dsPSecHy8JxevbT2q9Dgkg5O9DvExEXB1sMO0+N3sMbUWid+qL8c/ESJSzN0DA/F/o3vizR+PYt3uP5Qeh2TwctEjcXoUik1V7DFRm2F4ISJFPTwsGDE3dsazX+zHDwfOKD0OycAeE7U1hhciUpQkSXjuL30wOswPj364Fyl/FCg9EsnAHhO1JYYXIlKcViPh1fv6o1+QO2Yk7kFWfrHSI5EMDXpMW44oPQ7ZMIYXIrIKDnZarJgaAR9XPWLik3DWyDMs1OjugYFYMDoUb/6UxR5TS+H7GzXC8EJEVsPNyQ4J06NQbRaIXZUMY3ml0iORDLOHdUPskC7sMVGrYXghIqsS4O6IxLgonLpYitlrUmCqqlZ6JLKQJEl49q7e7DFRq7mu8LJkyRJIkoS5c+fWfW748OGQJKnBNnv27KvuJzY2ttFjRo8efT2jEZGK9fRzxYppEdjzx0U89Uk6zGaWP9WGPabrxJeKrkp2eElOTsby5csRHh7e6LaZM2ciLy+vblu6dOk19zd69OgGj/nwww/ljkZENmBwNy+8cX9/fJ1+Gv/+9pDS45AM7DFdB56tdVWywktxcTEmT56MFStWwMPDo9HtTk5O8PPzq9sMBsM196nX6xs8pqn9ElH7ckdff/zzL33wwW/H8cGvx5Qeh2Rwc7JDYlwUzEIgJj6JPabmqn/khUGmEVnhZc6cORgzZgxGjBjR5O3r1q2Dt7c3wsLCsHDhQpSWXvs9L7Zv3w4fHx/07NkTDz/8MC5cuCBnNCKyMTFDumD2sGD865tD2LTvtNLjkAz+bjU9ptOXyvDQavaY6PrpLH3Ahg0bkJqaiuTk5CZvnzRpEjp37oyAgACkp6djwYIFyMzMxOeff37FfY4ePRp33303unbtiuzsbDz99NO44447sHPnTmi12kb3N5lMMJn+9x4aRqPR0mUQkYosGN0T+cZyzPs4Dd7O9hgS4q30SGShHr41Paap8Ul46pN0vHF/f2g07HWQPBaFl5ycHDz++OPYsmULHBwcmrzPrFmz6j7u27cv/P39ER0djezsbAQHBzf5mAceeKDBY8LDwxEcHIzt27cjOjq60f0XL16MF154wZLRiUjFJEnCy/eE41yxCbPWpODjh25E74BrvxxN1qW2x/TI+lT4uurxzF29lR6JVMqil41SUlKQn5+PgQMHQqfTQafT4eeff8abb74JnU6H6urGhwIHDx4MAMjKymr21+nWrRu8vb2v+JiFCxeisLCwbsvJybFkGUSkQnZaDd6dMghdvZ0RuyoJOQXXfjmarA97TNQSLDryEh0djYyMjAafmz59OkJDQ7FgwYImX+JJS0sDAPj7+zf76+Tm5uLChQtXfIxer4der2/+4ERkE1z0OsTHRuLud39HzKokfDZ7CDyc7ZUeiywUM6QLzhjL8a9vDqGDqx7j+ndUeiRSGYuOvLi6uiIsLKzB5uzsDC8vL4SFhSE7OxuLFi1CSkoKTpw4gU2bNmHatGkYOnRog1OqQ0NDsXHjRgA1Zy7Nnz8fu3btwokTJ/Djjz9i3LhxCAkJwahRo1p2tUSkeh1c9VgdNxiXSivx4Oo9KK9k+VON/m9UT9w9sCOe+mQfdmSdV3oc68MzjK6qRa+wa29vj61bt2LkyJEIDQ3FvHnzMGHCBHz11VcN7peZmYnCwkIAgFarRXp6OsaOHYsePXpgxowZGDRoEH799VceXSGiJnX1dkZ8bCQOnjbi0Q/3oqrarPRIZCFJkvDyhHDc0M0Ls9ak4OBpnnhBzScJG3jfcqPRCDc3NxQWFjbrmjJEZBu2Hc7Hg6v34P7IILz01zBIvCqp6hSbqjDx/V04ayzHZw8PQZCnk9IjWYcL2YDXnye5FBwDPLspO08rkfv9m+9tRESqdWuoDxbf3Rfrd5/Esp+af1IAWY/aHpODnRYxq5JwsaRC6ZFIBRheiEjV7osIwrzbe+DVLUfwcTLPPFSjDq56JMZF4VJpJWYkJqOsgj0mujqGFyJSvb/dFoJJgzth4cYM/HT4rNLjkAy1PaZDeUXsMdE1MbwQkepJkoRF48JwW6gP5qzbi7ScS0qPRDL0D3LHO5MHYltmPp7bdAA2UMmkVsLwQkQ2QauRsGziAPQOMCAuIRnHzhUrPRLJwB4TNQfDCxHZDAc7LVbGRMDDyQ4xq5KQX1Su9EgkQ/0e00fJJ5Ueh6wQwwsR2RR3J3skxkXBVGlGXEIyik1VSo9EMvztthBMHtwJT2/czx4TNcLwQkQ2J9DDCQnTo/DH+VI8vDYFFVUsf6qNJEl4cVwYokN98Mi6VOw9eVHpkdoWr1l0VQwvRGSTegcYsHzqIOw6dgF//yyd5U8V0mokvDlxAPoEuGFG4h72mKgOwwsR2awhId7473398fneU3h5c6bS45AM7bbHxLB9VQwvRGTTxvYLwDNjeuG9n7OR8PtxpcchGWp7TBVV7bTHxCDTCMMLEdm8B2/phpm3dMULXx/Etxl5So9DMrDHRPUxvBBRu7Dwjl74S3gA5n6Uht3HLig9DsnQy9+A5dNqekwL2GNq1xheiKhd0GgkvHJvOCI6e+DB1XuQeaZI6ZFIhiHBNT2mjewxtWsML0TUbuh1WiyfOgiBHk6IiU/C6UtlSo9EMrDHRAwvRNSuuDrYIXF6JLQaCTHxSSgsrVR6JJKhfo/pm3T2mNobhhciand8DA5IjIvCuWITZq7eg/LKaqVHIhkW3tELY/sF4ImP0rDLlntMvGBdIwwvRNQuhfi4YGVMBPblXsITH6Wh2szyp9poNBJeuacfIrt6YCZ7TO0KwwsRtVuDOnvirUkD8f2BM3jxqwM8e0WF7HUavDeFPab2huGFiNq123v74l9/7YvEnX/g3Z+zlR6HZGCPqf1heCGidm/S4E54LLo7lm7OxGcpuUqPQzL4GByweoaN9ph4RLARhhciIgBPjOiOByKDsOCzdPx85JzS45AMwR1csDImEumnLmHuBpX3mLT2QJVJ6SmsFsMLEREASZLwr7+GYWiPDnh4bQoycguVHolkGNTZA8smDsQPB8/gBTX3mJw8gdICpaewWgwvRER/0mk1eGvSAHT3dcX0hCT8caFE6ZFIhtoe02o195hMRYDeVekprBbDCxFRPU72OsTHRMDVwQ4x8Uk4X8xD92qk+h5TRQlg76z0FFaL4YWI6DJeLnqsjotCsakaMxKSUWKqUnokkqF+j2l7Zr7S41iu9uJ0vEhdIwwvRERNCPJ0QsL0SGTlF2PO+lRUVpuVHoksVNtjGtajAx5Zl4r03EtKjySPWns7rYjhhYjoCsI6uuG9qYPw29Hz+MfGDPWWP9sxnVaDZZMGoIevK+ISktljshEML0REV3FL9w545d5wfLwnF69uOaL0OCSDk70OK9XYY6osr/mVobkRhhciomsYPyAQf78jFMt+ysLaXX8oPQ7JoLoek94AmP+8UjA7L40wvBARNcNDQ7shdkgXPPflfnx/4IzS45AMquoxSRpAWPF8CmN4ISJqBkmS8NxdvXFHmD8e+3Av9pzgBcTUqH6PaeHnVtxjkiSGl6tgeCEiaiaNRsJ/7+uH/kHumJG4B1n5RUqPRDLc0r0D/nNvP3yaYsU9JkkDmBleroThhYjIAg52Wrw/LQJ+BgfExCfjrLFc6ZFIhr8O6IiF1txj0umBapUUixXA8EJEZCE3RzskxEXCLARi4pNgLK9UeiSSYZY195jsHIHKMqWnsFoML0REMvi7OSIxLgqnL5Vh1uo9MFVVKz0SWUg1PSZ7Z8BUrPQUVoXhhYhIph6+rlgZG4nUk5cw7+N9MJuttPxJV3R5j+noWSvsMTn7ACXnlJ7CqjC8EBFdh8gunnjzgf74JiMPL317SOlxSIbaHpO/mwNi4pNwptDKekwanjZ9OYYXIqLrNDrMHy+M7YOVvx3Hil+OKT0OyeDmaIeE6VEAgNhV7DFZO4YXIqIWMO3GLnhkeDBe+vYQvkw7pfQ4JIOfmwMSrLHHZK3XolEQwwsRUQuZP6onJgwMxFOf7MPvWeeVHodkqN9jetJaekyVZTVnH1EdhhciohYiSRKWTOiLIcHeeGhNCg6cLlR6JJKhtsf0bUYe/vXNIeWvwitpePTlMgwvREQtyE6rwTuTB6KrtzNiVyUjp6BU6ZFIhtFh/nhxbB/E/34cH/x6XNlhNFpAWMlLWFaC4YWIqIU563WIj42Ek70WMauScLGkQumRSIapN3bBnFutoMckaQEzw0t9DC9ERK2gg6seidOjUFhaibjEZJRV8JuPGj010gp6TBoNAL5sVB/DCxFRK+ni7Yz42EgczivCox+moqqa1+pQG/aYrBPDCxFRK+oX5I53pgzEtsxzePbL/cqXP8litT2mbh3YY7IWDC9ERK3s1p4+WHJ3X3yYlIM3f8xSehySoUGPKT4JBewxKYrhhYioDdwbEYSnRvbAa1uPYEPSSaXHIRm8Xf7sMZVVYgZ7TIpieCEiaiNzbg3B1Bs64x9f7MePh84qPQ7JoFiPiS83NsDwQkTURiRJwj/H9sGIXj6Ysz4VqScvKj0SyaBIj0mSWv9rqAjDCxFRG9JqJLzxwACEBbhhRkIyjp0rVnokkqF+j+mNH48qPU67c13hZcmSJZAkCXPnzq373PDhwyFJUoNt9uzZzd7n7NmzIUkSXn/99esZjYjIajnYafFBTAS8XPSYFp+E/KJypUciGe6NCML8UT3x+tajrdNj4tGWK5IdXpKTk7F8+XKEh4c3um3mzJnIy8ur25YuXdqsfW7cuBG7du1CQECA3LGIiFTB3ckeiXFRqKw2Y/qqZBSVVyo9EsnwyPDg1usxsedyRbLCS3FxMSZPnowVK1bAw8Oj0e1OTk7w8/Or2wwGwzX3eerUKTz66KNYt24d7Ozs5IxFRKQqHd0dkRgXhZMXSvHw2lRUVPEidmrDHpMyZIWXOXPmYMyYMRgxYkSTt69btw7e3t4ICwvDwoULUVp69Qv6mM1mTJ06FfPnz0efPn2u+fVNJhOMRmODjYhIjUL9DHh/WgSSjhfg/z7dB7OZP22rzeU9pmz2mFqdxeFlw4YNSE1NxeLFi5u8fdKkSVi7di22bduGhQsXYs2aNZgyZcpV9/nyyy9Dp9Phsccea9YMixcvhpubW90WFBRk6TKIiKzGjcFeePX+fvhy32m8/P1hpcchGer3mGLik5BvZI+pNeksuXNOTg4ef/xxbNmyBQ4ODk3eZ9asWXUf9+3bF/7+/oiOjkZ2djaCg4Mb3T8lJQVvvPEGUlNTITWznLRw4UI8+eSTdb83Go0MMESkaneFByDfaMKLXx+En8EB02/qqvRIZKHaHtOEd3YgdlUyPnroBrg6sAbRGiw68pKSkoL8/HwMHDgQOp0OOp0OP//8M958803odDpUVze+2uDgwYMBAFlZTV8S+9dff0V+fj46depUt88//vgD8+bNQ5cuXZp8jF6vh8FgaLAREald3M1dMWtoN7z49UF8nX5a6XFIho7ujkiIi0ROQQv3mFjebcCiIy/R0dHIyMho8Lnp06cjNDQUCxYsgFarbfSYtLQ0AIC/v3+T+5w6dWqj7syoUaMwdepUTJ8+3ZLxiIhU7++jQ5FvLMeTH+2Dl7MeNwZ7KT0SWai2xxQTn4T/+3QfXr2vPzQanvbckiwKL66urggLC2vwOWdnZ3h5eSEsLAzZ2dlYv3497rzzTnh5eSE9PR1PPPEEhg4d2uCU6tDQUCxevBjjx4+Hl5cXvLwa/ue0s7ODn58fevbseR1LIyJSH41GwtJ7+uF8cQVmrdmDT2bfiFA/Hl1Wm9oe06Mf7oWvwQEL7+yl9Eg2pUWvsGtvb4+tW7di5MiRCA0Nxbx58zBhwgR89dVXDe6XmZmJwsLClvzSREQ2w16nwbtTBiLIwwkx8Uk4dalM6ZFIhrvCA/DsmN5Y/ssxxP92XOlxbIok2uRNGVqX0WiEm5sbCgsL2X8hIpuRX1SOu9/ZAUc7LT6ZfSPcneyVHolkWPztIbz/6zEsmzgAd4VbcBHWC9mAV3Djj22I3O/ffG8jIiIr5ePqgMS4KJwvNmHm6j0or2x8UgRZvwWjQzGuXwCe/GgfdmZfaP4D+fYAV8TwQkRkxYI7uGBlbCQyThXi8Q17Uc2L2KlObY8pqqsnZq3Zg8NneGHV68XwQkRk5QZ28sBbEwdiy8Gz+OemA7CBV/vbHfaYWhbDCxGRCozo7Yt/j++LNbv+wDvbs5Ueh2RwdbBDQlwk7LQaxMQn4VJphdIjqRbDCxGRSjwQ1QlzR3THK99n4tOUXKXHIRl8XB2wOi4KF4pNeDDxGj0mM9+o80oYXoiIVOTx6O6YGBWEBZ+lY3tmvtLjkAzd/uwx7T/NHpNcDC9ERCoiSRIWjQvDrT074JF1qdiXc0npkUiGZvWYeLbRFTG8EBGpjE6rwbKJA9HTzxVxCck4cb5E6ZFIBvaY5GN4ISJSIUd7LVbGRMLN0Q4xq5Jwvtik9EgkQ/0e0yd7chreaOcElJyv+VjSAJU8Q6kWwwsRkUp5OtsjMS4KpRXViEtIRompSumRSIbaHtPfP8/Atvo9JoM/UHap5mPPrkDhKUXms0YML0REKhbk6YRVsZE4dq4Ej6xLRWU1z1BRm/o9pjmX95jq917YganD8EJEpHJhHd3w3pRB2JF9Hn//LIMXsVMh9pgsw/BCRGQDbu7ujf/c2w+fpebiPz9kKj0OycAeU/MxvBAR2Yhx/Tvi6TtD8fa2bKzZeULpcUiGy3tMpRV8M86mMLwQEdmQmbd0Q9xNXfHcpgPYvP+M0uOQDEGeTkiYXtNjen7TAfaYmsDwQkRkQyRJwjNjeuHOvv54bMNeJJ8oUHokkqFPgBuWTx2E1JMXa3pMVSZAa6/0WFaD4YWIyMZoNBJeva8fBnZyx4yEZBw9W6T0SCTDTSHeWHhHKD5LzcVbm9MAvYvSI1kNhhciIhuk12nx/rQIBLg7IiY+CXmFvMCZGo3o5Yun7wzFht8OYW3qeaXHsRoML0RENsrgYIeE6VGQJAmx8ckoLKtUeiSSYWYfYOoATzz79RFs3p+n9DhWgeGFiMiG+bk5IDEuEmeM5Zi1eg9MVTx7RVW8giF5BWPWvX/BmL7+eGxDGntMYHghIrJ5IT6u+CAmAmk5l/Dkx/tgNvMidmqj0Uj4L3tMdRheiIjagcgunnjjgQH4LiMPi745yKvwqhB7TP/D8EJE1E6MDvPDC+PCsOr3E3j/l2NKj0MysMdUg+GFiKgdmXpDZ/zt1hAs/u4wNu7NVXockuHyHlN5ZfvrMTG8EBG1M/NG9sA9gwIx/5N0/Hr0nNLjkAwhPq5Y+WePaV477DExvBARtTOSJGHx3X1xc3dvzF6Tgv2nCpUeiWSI6OKJNycOwHf721+PieGFiKgdstNq8PakgQj2cUHsqmTkFJQqPRLJMKpP++wxMbwQEbVTznod4mMj4aLXYlp8EgpKKpQeiWRojz0mhhcionbM20WPxLgoFJVXIi4hGaUVVUqPRDLMG9kD97ajHhPDCxFRO9fZyxnxsZE4crYIj67fi6pqs9IjkYUkScK/21GPieGFiIgQHuiOdyYPxM9HzuGZL/a3q/KnrbDTavDO5IEIaQc9JoYXIiICAAzv6YMlE8KxITkHr289qvQ4JIOTvQ4r20GPieGFiIjq3DMoEPNH9cQbPx7F+t0nlR6HZGgPPSaGFyIiauCR4cGYdmNnPPNFBrYcPKv0OCSDrfeYGF6IiKgBSZLw/F/6YGRvPzz6YSpS/rio9EgkQ3igO96dMsgme0wML0RE1IhWI+H1B/qjb0c3PJiYjOxzxUqPRDIM69EBL9tgj4nhhYiImuRgp8UH0yLh7aLHtJVJyDeWKz0SyTDBBntMDC9ERHRFbk52SIyLQrVZIGZVMorKK5UeiWSwtR4TwwsREV1VgLsjEuOikHuxFLPXpqCiyrbKn+1BbY9pVB/b6DExvBAR0TX19HPFimkRSD5+EfM/3Qez2XbKn+2FViPhtfv7I7yjO2aovMfE8EJERM1yQzcvvHZ/f2zadxpLNh9WehySwcFOixXTItBB5T0mhhciImq2MeH+eO6u3nj/l2NY+dtxpcchGWyhx8TwQkREFpl+U1c8NKwbFn19EF/tO630OCSD2ntMDC9ERGSxBaNCMX5AR8z7eB92ZJ9XehySoX6P6alP1NVjYnghIiKLaTQSXp4QjsHdPPHQ6hQcyjMqPRLJcEM3L7z+QH98la6uHhPDCxERyWKv0+DdKYPQycsJsauScOpSmdIjkQx39vXH8yrrMTG8EBGRbC56HVZNj4S9ToOY+CRcKq1QeiSSIVZlPSaGFyIiui4+rg5InB6FgpIKzEjcg/LKaqVHIhnU1GNieCEiouvWrYMLVsZE4OBpIx77cC+qVVT+pBqX95gOnrbeHhPDCxERtYgBnTzw9uQB+PFwPp7ftB9CMMCoTW2PqbN3TY8p92Kp0iM1ieGFiIhazG2hvnjpr2FYu+sk3t6WpfQ4JIOLXof42Ejo7TSIXZVslT2m6wovS5YsgSRJmDt3bt3nhg8fDkmSGmyzZ8++6n7++c9/IjQ0FM7OzvDw8MCIESOwe/fu6xmNiIgU8kBUJzwxogf+88MRfLwnR+lxSAZr7zHJDi/JyclYvnw5wsPDG902c+ZM5OXl1W1Lly696r569OiBt956CxkZGfjtt9/QpUsXjBw5EufOnZM7HhERKeix6BBMjOqEhZ9nYNvhfKXHIRnq95ie/WK/0uM0ICu8FBcXY/LkyVixYgU8PDwa3e7k5AQ/P7+6zWAwXHV/kyZNwogRI9CtWzf06dMHr776KoxGI9LT0+WMR0RECpMkCYvG9cGtPX3wyLpUpOVcUnokkmFAJw/8c2xvfJKSi6TjBUqPU0dWeJkzZw7GjBmDESNGNHn7unXr4O3tjbCwMCxcuBClpc0v/FRUVOD999+Hm5sb+vXr1+R9TCYTjEZjg42IiKyLTqvBsokD0MvfFXEJyThxvkTpkUiG+yKC4O2ix/ZM6zmCZnF42bBhA1JTU7F48eImb580aRLWrl2Lbdu2YeHChVizZg2mTJlyzf1+/fXXcHFxgYODA1577TVs2bIF3t7eTd538eLFcHNzq9uCgoIsXQYREbUBR3stVsZEwt3JDtPik3CuyKT0SCSDTiPBms5+l4QF57Ll5OQgIiICW7Zsqeu6DB8+HP3798frr7/e5GN++uknREdHIysrC8HBwVfcd0lJCfLy8nD+/HmsWLECP/30E3bv3g0fH59G9zWZTDCZ/vcfwGg0IigoCIWFhdd8iYqIiNpeTkEp7n53B/wMDvhw1g1w0euUHoma6at9p/Hoh3uxdsZg3Ny96YMKchmNRri5uVn8/dui8PLFF19g/Pjx0Gq1dZ+rrq6GJEnQaDQwmUwNbgNqQomLiws2b96MUaNGNXuw7t27Iy4uDgsXLrzmfeUunoiI2s6B04W4f/kuhPi4ID42Ep7O9kqPRNewPTMfj6xLxfCeHfDO5EEtvn+5378tetkoOjoaGRkZSEtLq9siIiIwefJkpKWlNQouAJCWlgYA8Pf3t+RLwWw2Nzi6QkRE6tYnwA3rZw5G7sVS/GXZb9h68KzSI9EVlFVUY8l3hzEjcQ+GBHvhv/f2V3qkBiw6bufq6oqwsLAGn3N2doaXlxfCwsKQnZ2N9evX484774SXlxfS09PxxBNPYOjQoQ1OqQ4NDcXixYsxfvx4lJSU4KWXXsLYsWPh7++P8+fP4+2338apU6dw7733tswqiYjIKoQHuuOLOTfh6Y378eDqPRjWowPm3BqCqK6eSo9GAMorq/FJSi7e256Nc8UmzI3ujoeHB0Onta5r2rboi4729vbYunUrXn/9dZSUlCAoKAgTJkzAM8880+B+mZmZKCwsBABotVocPnwYiYmJOH/+PLy8vBAZGYlff/0Vffr0acnxiIjICgR6OCFxeiS+zTiDN348gvuW78TATu54ILIT7gz3Zx9GAdnnivFZSi4+3pOLghITxoQH4Mnbe6Crt7PSozXJos6LtWLnhYhIncxmgZ8O5yNx5wn8lnUeep0GI3r54vbevhjewwduTnZKj2iThBDIPleMLQfz8f2BM0jLuQSDgw7j+nfEjJu7oksbhZY2KexaK4YXIiL1O32pDBv3nsJ3+/Ow/5QRWo2EQZ09cGM3Lwzu5omBnTzgYNe4W0nNk28sx67jBdh17AJ2ZJ3HiQulcLTT4ubu3vhr/46I7uXT5n++DC8ML0RENiOvsAw/HsrHz0fOIel4AQrLKmGv1SCsowF9O7qhb6A7wgPdENzBBVqNpPS4VqfYVIUDpwqRcaoQ6bmFSM+9hBMXai4YG9zBGTcGeyE61Bc3BnspGggZXhheiIhsktkskHm2CLuPXcDenEvIOFWIY+dqrtZrr9MguIMLevi6oLuPC0J8XNDZyxmdPJ3gbOPdGSEEzhWbkFNQimPnSpCVX4wjZ4tw5GwxTl0qAwA42GnQJ8ANfTu6IbKLJ6K6eqKDq17hyf+H4YXhhYio3TCWV2L/qUIczivC0fxiHD1bhCNni2Asr6q7j7eLPYI8nRDo4QQ/gx6+Bgf4uTnAz+AAH1cHeLrYw9leC0myviM31WaBwrJKFJSYcKbQhDPGcpw1liOvsAxnCsuRU1CGkwWlKKv3bs9Bno7o7uOK7r4u6O7jirCOBoR0cLG6M4XqY3hheCEiateEEDhfXIGTBaU4WVCCkxdqvsHnXizFWWM5zhjLUV5pbvAYe50Gnk728HC2h4eTHVwddHDR1/6qg4uDDg46DRzstNDbaeCgq/nVTquBRpKgkSRoNRK0mpo3ozSbBarNAtVCwGwGqoVARZUZpqpqlFf+79fyymoYyytRXF6FYlMVisqrUFReiYKSChSUVOBSWSUu/+7s4WQHX4MD/N0cEOTphE5/bp29nBHk6Qgne/UdaZL7/Vt9KyUiImqCJEno4KpHB1c9BnX2aHS7EALGsiqcMZbjXJEJBaUVuPhnWCgoqcDF0goUm6pwobikQaAwVZlhqjI38RUtp5EABzstHOy0dQGpNjAFejghPNAdns728HS2h4eTPbxc7OHr6gAfg55l5XoYXoiIqF2QJAluTnZwc7JDTz9Xix5rNgtUVJthqjSjvKoaldVmCIG6oyxCCJhFTTipPRpT+6u9TgP9n0dvdBrJKl+mUhuGFyIiomvQaCQ4aGqOmLiB155RmvW2eIiIiIiawPBCREREqsLwQkRERKrC8EJERESqwvBCREREqsLwQkRERKrC8EJERESqwvBCREREqsLwQkRERKrC8EJERESqwvBCREREqsLwQkRERKrC8EJERESqYhPvKi2EAAAYjUaFJyEiIqLmqv2+Xft9vLlsIrwUFRUBAIKCghSehIiIiCxVVFQENze3Zt9fEpbGHStkNptx+vRpuLq6QpKkNvmaRqMRQUFByMnJgcFgaJOv2ZZseX22vDbAttdny2sDuD41s+W1Aa23PiEEioqKEBAQAI2m+U0WmzjyotFoEBgYqMjXNhgMNvkPtZYtr8+W1wbY9vpseW0A16dmtrw2oHXWZ8kRl1os7BIREZGqMLwQERGRqjC8yKTX6/H8889Dr9crPUqrsOX12fLaANteny2vDeD61MyW1wZY3/psorBLRERE7QePvBAREZGqMLwQERGRqjC8EBERkaowvBAREZGqMLz8KTU1Fbfffjvc3d3h5eWFWbNmobi4uNH9EhISEB4eDgcHB/j4+GDOnDnX3PfOnTtx2223wdnZGQaDAUOHDkVZWVmj+5lMJvTv3x+SJCEtLa0llgVAubWdOHECM2bMQNeuXeHo6Ijg4GA8//zzqKioaLG1Kbk+ACgoKMDkyZNhMBjg7u6OGTNmNPm1rXF9w4cPhyRJDbbZs2c3uE9ycjKio6Ph7u4ODw8PjBo1Cvv27bOJtcnZr6WUXh8AXLhwAYGBgZAkCZcuXWqJZdVRan379u3DxIkTERQUBEdHR/Tq1QtvvPGGTawNAE6ePIkxY8bAyckJPj4+mD9/PqqqqlSxvlpCCNxxxx2QJAlffPFFg9ta5HlFkDh16pTw8PAQs2fPFocPHxZJSUliyJAhYsKECQ3u99///lcEBASIdevWiaysLLFv3z7x5ZdfXnXfO3bsEAaDQSxevFjs379fHD58WHz00UeivLy80X0fe+wxcccddwgAYu/evapf23fffSdiY2PF999/L7Kzs8WXX34pfHx8xLx581pkbUqvTwghRo8eLfr16yd27dolfv31VxESEiImTpyoivUNGzZMzJw5U+Tl5dVthYWFdbcXFRUJT09PERsbKw4fPiz2798vJkyYIHx9fUVFRYWq1yZ3v2paX61x48bVPa9cvHixpZan6PpWrlwpHnvsMbF9+3aRnZ0t1qxZIxwdHcWyZctUv7aqqioRFhYmRowYIfbu3Su+/fZb4e3tLRYuXNgia2vt9dV69dVX6/7dbdy4se7zLfW8wvAihFi+fLnw8fER1dXVdZ9LT08XAMTRo0eFEEIUFBQIR0dHsXXrVov2PXjwYPHMM89c837ffvutCA0NFQcOHGjR8GINa6tv6dKlomvXrhY95mqUXN/BgwcFAJGcnFz3ue+++05IkiROnTpl4Uqa1prrGzZsmHj88ceveHtycrIAIE6ePHnFr309lFyb3P1aQsn11XrnnXfEsGHDxI8//tji4cUa1lffI488Im699VaLHnMlSq7t22+/FRqNRpw5c6buc++++64wGAzCZDJZtpAraM31CSHE3r17RceOHUVeXl6j8NJSzyt82Qg1L9fY29s3eFMoR0dHAMBvv/0GANiyZQvMZjNOnTqFXr16ITAwEPfddx9ycnKuuN/8/Hzs3r0bPj4+GDJkCHx9fTFs2LC6fdY6e/YsZs6ciTVr1sDJycmm1na5wsJCeHp6tsDKaii5vp07d8Ld3R0RERF1nxsxYgQ0Gg12795t1eurtW7dOnh7eyMsLAwLFy5EaWlp3W09e/aEl5cXVq5ciYqKCpSVlWHlypXo1asXunTpouq1Xc9+1bA+ADh48CBefPFFrF692qI3vGsupdd3uZZ8blFybTt37kTfvn3h6+tb97lRo0bBaDTiwIEDVr++0tJSTJo0CW+//Tb8/Pwa3d5izysWRyobtH//fqHT6cTSpUuFyWQSBQUFYsKECQKA+Pe//y2EEGLx4sXCzs5O9OzZU2zevFns3LlTREdHi549e14xDe/cuVMAEJ6eniI+Pl6kpqaKuXPnCnt7e3HkyBEhhBBms1mMHj1aLFq0SAghxPHjx1v0yIuSa7vc0aNHhcFgEO+//36LrE3p9b300kuiR48ejR7boUMH8c4771j1+oSo+elr8+bNIj09Xaxdu1Z07NhRjB8/vsF9MjIyRHBwsNBoNEKj0YiePXuKEydOqH5tcverlvWVl5eL8PBwsWbNGiGEENu2bWvxIy9K/9us7/fffxc6nU58//33ql/bzJkzxciRIxs8pqSkRAAQ3377rdWvb9asWWLGjBl1v8dlR16EaJnnFZsOLwsWLBAArrodOnRICCHEunXrhK+vr9BqtcLe3l489dRTwtfXVyxZskQIUfONCkCD/xz5+flCo9GIzZs3N/n1f//9dwGg0WuVffv2FX//+9+FEEK88cYb4qabbhJVVVVCiOaHFzWsrb7c3FwRHBzc4B+12td3PeFF6fU1pfalhaysLCGEEKWlpSIqKkpMmzZNJCUliZ07d4oJEyaIPn36iNLSUlWv7Xr2q4b1PfHEE+L++++vu92S8KKG9dWXkZEhvL29634AVPvarie8KL2+L7/8UoSEhIiioqK6z10eXuQ+r1zOpsNLfn6+OHTo0FW3yxPkmTNnRFFRkSguLhYajUZ8/PHHQggh4uPjBQCRk5PT4P4+Pj5XPJJw7NgxAaDup59a9913n5g0aZIQoqZMp9FohFarrdsACK1WK6ZNm6bqtdU6deqU6N69u5g6dWqD11ivRg3rW7lypXB3d29we2VlpdBqteLzzz+36vU1pbi4WACoe2L64IMPGr0ubjKZhJOTk/jwww9Vvbbr2a8a1tevX78GzysajabueeW5555T/fpqHThwQPj4+Iinn366WftRw9qeffZZ0a9fvwb3qX0+Sk1Nter1Pf7440KSpEbfzzQajRg2bJgQQv7zyuVsOrxcj5UrVwonJ6e6n1QyMzMFgAblpQsXLgiNRnPFQ5Vms1kEBAQ0Kn3279+/7if6P/74Q2RkZNRt33//vQAgPv3000b/aNS2NiFqjrh0795dPPDAA3VHl1pbW62vtrC7Z8+eutu///77Fi3sNqUl1teU3377TQAQ+/btE0II8eabbwo/Pz9hNpvr7lNZWSmcnZ3FunXrWmYxl2mrtbXUfi3VVuvLyspq8LxS+41ox44d4uzZsy26pvraan1C1Lz04ePjI+bPn99i819NW62ttrBb/+9p+fLlwmAwNHmWaktpifXl5eU1+HeXkZEhAIg33nhDHDt2TAjRcs8rDC9/WrZsmUhJSRGZmZnirbfeEo6OjuKNN95ocJ9x48aJPn36iN9//11kZGSIu+66S/Tu3bvu9K7c3FzRs2dPsXv37rrHvPbaa8JgMIhPPvlEHD16VDzzzDPCwcGhycOfQrR850XJteXm5oqQkBARHR0tcnNzG5wa2JKU/LsbPXq0GDBggNi9e7f47bffRPfu3Vv0VOnWWl9WVpZ48cUXxZ49e8Tx48fFl19+Kbp16yaGDh1at89Dhw4JvV4vHn74YXHw4EGxf/9+MWXKFOHm5iZOnz6t6rU1Z79qX199rdF5UXJ9GRkZokOHDmLKlCkNnlfy8/NVv7baU6VHjhwp0tLSxObNm0WHDh1a9FTp1lpfUy5/2ailnlcYXv40depU4enpKezt7UV4eLhYvXp1o/sUFhaKuLg44e7uLjw9PcX48eMbnO5VGzy2bdvW4HGLFy8WgYGBwsnJSdx4443i119/veIcrRFelFrbqlWrrvi6a0tS8u/uwoULYuLEicLFxUUYDAYxffr0Bq/3Wuv6Tp48KYYOHSo8PT2FXq8XISEhYv78+Y2uFfLDDz+Im266Sbi5uQkPDw9x2223iZ07d9rE2q61X7Wvr77WCi9Kre/5559v8nmlc+fOql+bEEKcOHFC3HHHHcLR0VF4e3uLefPmicrKyhZbW2utrymXhxchWuZ5Rfpz50RERESqwOu8EBERkaowvBAREZGqMLwQERGRqjC8EBERkaowvBAREZGqMLwQERGRqjC8EBERkaowvBAREZGqMLwQERGRqjC8EBERkaowvBAREZGqMLwQERGRqvw/YnVJClfjJ54AAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "These are your orig (faint) and squished shapes for clip no 3 out of 3\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 when ready 1\n"
     ]
    }
   ],
   "source": [
    "#starting with MN, we moved the \"option2\" block earlier in the notebook, as we run it before running option 1 (as in other states)\n",
    "print(\"for some states like FL, MD, MN we move in partial counties via clipPoly's before running option 2\")\n",
    "vtdCP = tractCP.copy()\n",
    "#CODE TO SQUISH GEOMETRIES FROM CLIP LINES INTO THE MAP\n",
    "print(\"adding code here to 'push in' state panhandles ...\")\n",
    "trimDF = pd.read_csv(\"state_map_files/cutNclipPolyLists.csv\")\n",
    "stateRows = trimDF[\"state\"].to_list()\n",
    "DFrow = stateRows.index(STATE)\n",
    "nClips = trimDF[\"nClipPoly\"][DFrow]\n",
    "nCuts  = trimDF[\"nCutPoly\"][DFrow]\n",
    "#Adding in here trimming ops\n",
    "toSquishUnitsList = list()\n",
    "toSquishGeomsList = list()  #combined list of geoms we will squish (over all squish operations)\n",
    "toSquishCountiesList = list()\n",
    "squishedShapesList = list()   #unit shapes after squishing, list over all squish operations\n",
    "if nClips > 0:\n",
    "    clipPoints = ast.literal_eval(trimDF[\"clipPoints\"][DFrow])   #sets of four points\n",
    "    farPoints  = ast.literal_eval(trimDF[\"farPoints\"][DFrow])    #pairs of points\n",
    "    newFarPoints  = ast.literal_eval(trimDF[\"newFarPoints\"][DFrow])   #pairs\n",
    "    cPts = [Point(clipPoints[i][0],clipPoints[i][1]) for i in range(len(clipPoints)) ]\n",
    "    fPts = [Point(farPoints[i][0],farPoints[i][1]) for i in range(len(farPoints)) ]\n",
    "    nfPts = [Point(newFarPoints[i][0],newFarPoints[i][1]) for i in range(len(newFarPoints)) ]\n",
    "    \n",
    "    for clipNo in range(nClips):\n",
    "        print(\"performing squish no\",clipNo+1,\"for state\",STATE)\n",
    "        n0,n1,n2,n3 = int(4*clipNo), int(4*clipNo+1), int(4*clipNo+2), int(4*clipNo+3)\n",
    "        clipPoly = Polygon([cPts[n0],cPts[n1],cPts[n2],cPts[n3] ] )\n",
    "        cutLine = LineString([cPts[n0],cPts[n1]] )\n",
    "        farLine = LineString([fPts[int(2*clipNo)],fPts[int(2*clipNo+1)] ] )\n",
    "        newFarLine = LineString([nfPts[int(2*clipNo)],nfPts[int(2*clipNo+1)] ])\n",
    "        \n",
    "        toSquishCounties = list()\n",
    "        toSquishUnits = list()\n",
    "        for c in range(nCounties):\n",
    "            if clipPoly.intersects(countyGeom[c]):\n",
    "                toSquishCounties.append(c)\n",
    "                if clipPoly.contains(countyGeom[c]):\n",
    "                    toSquishUnits = toSquishUnits + countyTractList[c]\n",
    "                else:\n",
    "                    for t in countyTractList[c]:\n",
    "                        if clipPoly.contains(vtdCP[t]):\n",
    "                            toSquishUnits.append(t)\n",
    "        print(\"clipPoly\",clipNo,\"intersects\",toSquishCounties,\"counties and a total of\",len(toSquishUnits),\"units\")\n",
    "        toSquishGeomUnion = vtdGeom[toSquishUnits[0]]\n",
    "        toSquishGeoms = list()\n",
    "        for t in toSquishUnits:\n",
    "            toSquishGeomUnion = toSquishGeomUnion.union(vtdGeom[t])\n",
    "            toSquishGeoms.append(vtdGeom[t])\n",
    "        unclippedGeom = MAP.difference(toSquishGeomUnion)\n",
    "        altCutLine = toSquishGeomUnion.buffer(0.001).intersection(unclippedGeom)\n",
    "        print(\"Here is the original cutLine and an alternate based on cut shapes\")\n",
    "        #plotPoly(MAP,0.1)\n",
    "        plotPoly(cutLine.buffer(0.02))\n",
    "        plotPoly(altCutLine,0.1)\n",
    "        plt.show()\n",
    "        # could use altCutLine for a more accurate squish at the squish-no_squish boundary ...\n",
    "        #newShapes = squish(clippedGeomList, altCutLine, farLine, newFarLine)\n",
    "        squishedShapes = squish(toSquishGeoms, cutLine, farLine, newFarLine) #..but may distort results\n",
    "        toSquishUnitsList.append(toSquishUnits)\n",
    "        toSquishGeomsList.append(toSquishGeoms)\n",
    "        toSquishCountiesList.append(toSquishCounties)\n",
    "        squishedShapesList.append(squishedShapes)\n",
    "        for geo in toSquishGeoms:\n",
    "            plotPoly(geo,0.1)\n",
    "            plotPoly(geo.centroid.buffer(0.004),0.1)\n",
    "        for geo in squishedShapes:\n",
    "            plotPoly(geo)\n",
    "            plotPoly(geo.centroid.buffer(0.002),0.4)\n",
    "        print(\"These are your orig (faint) and squished shapes for clip no\",clipNo+1,\"out of\",nClips)\n",
    "        plt.show()\n",
    "        pause = input(\"enter 1 when ready\")    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "62667c48-6c66-4381-b01d-518af61651bd",
   "metadata": {},
   "outputs": [],
   "source": [
    "#now apply the squish to all impacted vtds.  \"tractGeom\" will retain original vtd shapes, so we can reset if needed\n",
    "for i, vList in enumerate(toSquishUnitsList):\n",
    "    squishedShapes = squishedShapesList[i]\n",
    "    for j, v in enumerate(vList):\n",
    "        vtdGeom[v] = squishedShapes[j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9715564f-3b60-43e5-9f1f-02f3dcee3933",
   "metadata": {},
   "outputs": [],
   "source": [
    "c = 22  #pick a county for visualization if desired\n",
    "print(\"here are the faint(original) and squished shapes for county\",c)\n",
    "for t in countyTractList[c]:\n",
    "    plotPoly(vtdGeom[t])\n",
    "    plotPoly(tractGeom[t],0.1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "760bc48e-0236-4ad7-b3b8-d74795009f53",
   "metadata": {},
   "outputs": [],
   "source": [
    "print(\"alternate simple approach for Florida Keys - translate all toward county CP\")\n",
    "c = 43\n",
    "vtdGeom = tractGeom.copy()  #a reset\n",
    "nTranslated = 0\n",
    "newCP = Point(-81, 25.1)\n",
    "for v in countyTractList[c]:\n",
    "    if clipPoly.contains(tractCP[v]):\n",
    "        xDelta, yDelta = newCP.x - tractCP[v].x, newCP.y - tractCP[v].y\n",
    "        xOFF, yOFF = 0.95 * xDelta, 0.95 * yDelta\n",
    "        vtdGeom[v] = translate(vtdGeom[v],xoff= xOFF, yoff=yOFF)\n",
    "        nTranslated +=1\n",
    "print(\"I translated\",nTranslated,\"vtds toward the center of county\",c)\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]\n",
    "countyGeom[c] = vtdGeom[countyTractList[c][0]]\n",
    "for v in countyTractList[c]:\n",
    "    countyGeom[c] = countyGeom[c].union(vtdGeom[v])\n",
    "    plotPoly(hdCP[v].buffer(0.03))\n",
    "plotPoly(countyGeom[c])\n",
    "unsquishedMAP = MAP\n",
    "MAP = countyGeom[uncutCountyList[0]]\n",
    "for c in uncutCountyList:\n",
    "    MAP = MAP.union(countyGeom[c])\n",
    "#plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "4ef91f8f-dabb-4c58-a8a4-bba8e725e586",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to use shifted shapes (e.g. for MD, MN), else enter 0 for most states to use uncut counties 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on confirming HD center 0 is inside the map's convex hull\n",
      "working on confirming HD center 501 is inside the map's convex hull\n",
      "working on confirming HD center 1001 is inside the map's convex hull\n",
      "working on confirming HD center 1501 is inside the map's convex hull\n",
      "working on confirming HD center 2003 is inside the map's convex hull\n",
      "working on confirming HD center 2503 is inside the map's convex hull\n",
      "working on confirming HD center 3003 is inside the map's convex hull\n",
      "working on confirming HD center 3503 is inside the map's convex hull\n",
      "working on confirming HD center 4004 is inside the map's convex hull\n",
      "Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Note the MAP convex hull.  Overwrite with your own polygon if desired.\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 - draw polygonal HDs.  #REQUIRES CONSISTENT TREATMENT OF CCB'S \n",
    "#For GA, MA, MD, MN we draw HDs for ALL vtds, even if they are in a CCB.  We use the clipPoly's to squish in the corners for these HD shapes\n",
    "#Not sure if below would work if we have cut districts AND squished-in corners\n",
    "#We normally draw for each (squished or orig) vtd.  Or, read in tract or blockgroup geometries, use those pops and unit centerpoints\n",
    "\n",
    "hdCP = [vtdGeom[v].centroid for v in range(nTracts)]  #remember, this is after any squish operation\n",
    "print(\"Here we compute the map's convex hull. We can build out of whole counties or after squish operations.\")\n",
    "useSquish = int(input(\"enter 1 to use shifted shapes (e.g. for MD, MN), else enter 0 for most states to use uncut counties\"))\n",
    "if useSquish == 1:\n",
    "    convexMAP = hdCP[0].buffer(0.1)\n",
    "    for v in range(nTracts):\n",
    "        if v not in skipList:\n",
    "            convexMAP = convexMAP.union(hdCP[v].buffer(0.1))\n",
    "else:  #build the map via simple union of counties not wholly in fully cut-out districts\n",
    "    convexMAP = countyGeom[uncutCountyList[0]]\n",
    "    for c in uncutCountyList:\n",
    "        convexMAP = convexMAP.union(countyGeom[c])\n",
    "    #convexMAP = MAP.centroid\n",
    "    #for c in range(nCounties):\n",
    "    #    if c not in allFusedCounties:\n",
    "    #        convexMAP = convexMAP.union(countyGeom[c])\n",
    "MAPhull = convexMAP.convex_hull.buffer(0.01*convexMAP.area**0.5)\n",
    "plotPoly(MAPhull)\n",
    "popHDlist = list()\n",
    "for t in range(nTracts):\n",
    "    if t not in allCutVTDs and t not in skipList:  #keep low-pop tracts as VEST may have assigned voters to them\n",
    "        popHDlist.append(t)\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on confirming HD center\",t,\"is inside the map's convex hull\")\n",
    "    if hdCP[t].disjoint(convexMAP.convex_hull):\n",
    "        plotPoly(hdCP[t].buffer(0.03))\n",
    "        hdCP[t] = nearest_points(convexMAP.convex_hull,hdCP[t])[0]\n",
    "        plotCenter(\"m\",hdCP[t])\n",
    "    else:\n",
    "        plotPoly(hdCP[t].buffer(0.01))\n",
    "plotPoly(convexMAP)\n",
    "plotPoly(convexMAP.convex_hull)\n",
    "plotPoly(MAPhull)\n",
    "for c in allFusedCounties:\n",
    "    plotPoly(countyGeom[c],0.2)\n",
    "print(\"Here is the convex hull and shape and a dot map of the (shifted) unit centerpoints\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Note the MAP convex hull.  Overwrite with your own polygon if desired.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "8393e96a-75c6-48ec-94e8-1f6fe58d31df",
   "metadata": {},
   "outputs": [],
   "source": [
    "nHDs = nTracts  #need to run this if we start option 2 from a vest list, not a previously run HD poly list\n",
    "HDcountyNo = countyNo.copy()\n",
    "populatedTractList = popHDlist.copy()  #nomenclature equivalency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "bcaf6ea2-1c3b-48c1-9ad6-937d7b7e4385",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\n",
      "working on tract-tract distances for unit 0 out of 4110 . Time = 0\n",
      "working on tract-tract distances for unit 401 out of 4110 . Time = 76\n",
      "working on tract-tract distances for unit 801 out of 4110 . Time = 143\n",
      "working on tract-tract distances for unit 1201 out of 4110 . Time = 207\n",
      "working on tract-tract distances for unit 1601 out of 4110 . Time = 267\n",
      "working on tract-tract distances for unit 2003 out of 4110 . Time = 311\n",
      "working on tract-tract distances for unit 2403 out of 4110 . Time = 348\n",
      "working on tract-tract distances for unit 2803 out of 4110 . Time = 377\n",
      "working on tract-tract distances for unit 3203 out of 4110 . Time = 397\n",
      "working on tract-tract distances for unit 3603 out of 4110 . Time = 411\n",
      "working on tract-tract distances for unit 4004 out of 4110 . Time = 417\n",
      "All done; total elapsed  417 seconds for MN with 8 districts to map\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "our maxD was 6.222000052695625\n"
     ]
    }
   ],
   "source": [
    "#continuing option 2 ....... ##########  THIS IS FOR TRACT - TRACT, despite the \"unit\" nomenclature\n",
    "print(\"Let us establish the (post-squish) point-point distances for all HD centers, about 8 min for 4000-unit state\")\n",
    "#NOTE: FOR LARGE STATES, RESTRICT THE SEARCH TO COUNTIES WITHIN A 3/SQRT(nDistrict) DIAMETER OF THE HOME UNIT\n",
    "uuDist = [[int(maxD+1) for t in range(nHDs)] for t in range(nHDs)] #default: too big to capture\n",
    "closeCountyList = [list() for c in range(nCounties)]\n",
    "closeCountyDist = maxD   #min(maxD,3./float(nDistricts)**0.5 * maxD )  #use above maxD for these counties as well\n",
    "xScaleSquared = xScale*xScale\n",
    "if nDistricts < 10: #closeCountyDist >= maxD:  #small state\n",
    "    closeCountyList = [[i for i in range(nCounties)] for c in range(nCounties)]  #all counties are close enough\n",
    "else:\n",
    "    for c in uncutCountyList:\n",
    "        closeCountyList[c].append(c)\n",
    "        for cc in range(c+1,nCounties):\n",
    "            if cc in uncutCountyList:\n",
    "                if cc in neighborCountyList[c]:\n",
    "                    closeCountyList[c].append(cc)\n",
    "                    closeCountyList[cc].append(c)\n",
    "                else:    \n",
    "                    dist = getLongDist(countyCP[c], countyCP[cc],xScale)\n",
    "                    if dist < closeCountyDist:\n",
    "                        closeCountyList[c].append(cc)\n",
    "                        closeCountyList[cc].append(c)\n",
    "startTime = time.time()\n",
    "\n",
    "for i,t in enumerate(populatedTractList):\n",
    "    if i %400 == 0:\n",
    "        print(\"working on tract-tract distances for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime))\n",
    "    uuDist[t][t] == 0.\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "                dist = getLongDist(hdCP[t], hdCP[tt],xScale)\n",
    "                uuDist[t][tt], uuDist[tt][t] = dist, dist\n",
    "print(\"All done; total elapsed \",int(time.time()-startTime),\"seconds for\",STATE,\"with\",nDistricts,\"districts to map\" )\n",
    "plt.hist(uuDist)\n",
    "plt.show()\n",
    "print(\"our maxD was\",maxD)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "2f392acb-ba52-4343-80ae-a58ba0b57366",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "similar to above, but for angles\n",
      "working on unit-unit angles for unit 0 out of 4110 . Time = 0\n",
      "working on unit-unit angles for unit 200 out of 4110 . Time = 20\n",
      "working on unit-unit angles for unit 401 out of 4110 . Time = 39\n",
      "working on unit-unit angles for unit 601 out of 4110 . Time = 57\n",
      "working on unit-unit angles for unit 801 out of 4110 . Time = 74\n",
      "working on unit-unit angles for unit 1001 out of 4110 . Time = 90\n",
      "working on unit-unit angles for unit 1201 out of 4110 . Time = 106\n",
      "working on unit-unit angles for unit 1401 out of 4110 . Time = 120\n",
      "working on unit-unit angles for unit 1601 out of 4110 . Time = 132\n",
      "working on unit-unit angles for unit 1802 out of 4110 . Time = 144\n",
      "working on unit-unit angles for unit 2003 out of 4110 . Time = 155\n",
      "working on unit-unit angles for unit 2203 out of 4110 . Time = 165\n",
      "working on unit-unit angles for unit 2403 out of 4110 . Time = 174\n",
      "working on unit-unit angles for unit 2603 out of 4110 . Time = 182\n",
      "working on unit-unit angles for unit 2803 out of 4110 . Time = 189\n",
      "working on unit-unit angles for unit 3003 out of 4110 . Time = 194\n",
      "working on unit-unit angles for unit 3203 out of 4110 . Time = 199\n",
      "working on unit-unit angles for unit 3403 out of 4110 . Time = 203\n",
      "working on unit-unit angles for unit 3603 out of 4110 . Time = 206\n",
      "working on unit-unit angles for unit 3803 out of 4110 . Time = 209\n",
      "working on unit-unit angles for unit 4004 out of 4110 . Time = 211\n",
      "All done with angles; total elapsed seconds = 211\n"
     ]
    },
    {
     "data": {
      "image/png": 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cAgwAADAOAQYAABiHAAMA6DLfPPlRoFto1b7hIwLdAvxAgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAgG4pOzu7w9ZVVHxlh60LbUOAAQAAxiHAAAAA4/gVYHJycnT99derX79+iomJ0d133639+/f71EyYMEFhYWE+06xZs3xqKisrlZ6erj59+igmJkbz58/X6dOnfWq2bdum0aNHy2azaejQocrNzW3fFgIAgJDjV4ApKSlRRkaGdu7cqcLCQp06dUqTJk1SXV2dT92jjz6qI0eOWNOyZcusZY2NjUpPT1dDQ4N27NihtWvXKjc3V4sXL7ZqDh06pPT0dN1yyy0qLy/X3Llz9cgjj6igoOAiNxcAAISCCH+Kt27d6vN3bm6uYmJiVFZWpvHjx1vz+/TpI4fD0eI63n//fX355Zf64IMPFBsbq2uvvVZPP/20Fi5cqOzsbEVGRmrNmjVKTEzU8uXLJUkjRozQxx9/rBUrVsjlcvm7jQAAIMRc1DEwtbW1kqTo6Gif+evWrdPAgQM1cuRIZWVl6e9//7u1rLS0VMnJyYqNjbXmuVwueTwe7d2716pJS0vzWafL5VJpaWmrvdTX18vj8fhMAAAgNPk1AnOmpqYmzZ07VzfeeKNGjhxpzb///vs1ZMgQxcfH64svvtDChQu1f/9+vf3225Ikt9vtE14kWX+73e7z1ng8Hp04cUK9e/c+p5+cnBw99dRT7d0cAABgkHYHmIyMDO3Zs0cff/yxz/zHHnvM+ndycrLi4uI0ceJEHTx4UFde2XnnyWdlZSkzM9P62+PxKCEhodPuDwAABE67diHNmTNHeXl5+vDDDzVo0KDz1o4dO1aSdODAAUmSw+FQdXW1T03z383HzbRWY7fbWxx9kSSbzSa73e4zAQCA0ORXgPF6vZozZ442bdqk4uJiJSYmXvA25eXlkqS4uDhJktPpVEVFhWpqaqyawsJC2e12JSUlWTVFRUU+6yksLJTT6fSnXQAAEKL8CjAZGRn63e9+p/Xr16tfv35yu91yu906ceKEJOngwYN6+umnVVZWpq+//lrvvvuupk+frvHjxyslJUWSNGnSJCUlJenBBx/Un/70JxUUFGjRokXKyMiQzWaTJM2aNUt/+ctftGDBAv35z3/WK6+8oo0bN2revHkdvPkAgK6wb/iIQLeAEONXgFm9erVqa2s1YcIExcXFWdObb74pSYqMjNQHH3ygSZMmafjw4frFL36hKVOmaPPmzdY6wsPDlZeXp/DwcDmdTj3wwAOaPn26li5datUkJiYqPz9fhYWFGjVqlJYvX67XXnuNU6gBAIAkPw/i9Xq9512ekJCgkpKSC65nyJAheu+9985bM2HCBH3++ef+tAcAALoJfgsJAAAYhwADAACMQ4ABAADGIcAAAADjEGAAAIBxCDAAAMA4BBgAAGAcAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwgOmyowLdAQB0OQIMAAAwDgEGAAAYhwADAEAHuPzJ/EC30K0QYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BBgAAGIcAAwAAjEOAAQAAxvErwOTk5Oj6669Xv379FBMTo7vvvlv79+/3qTl58qQyMjI0YMAA9e3bV1OmTFF1dbVPTWVlpdLT09WnTx/FxMRo/vz5On36tE/Ntm3bNHr0aNlsNg0dOlS5ubnt20IAkqTs7OxAtwAAHcavAFNSUqKMjAzt3LlThYWFOnXqlCZNmqS6ujqrZt68edq8ebPeeustlZSU6PDhw7rnnnus5Y2NjUpPT1dDQ4N27NihtWvXKjc3V4sXL7ZqDh06pPT0dN1yyy0qLy/X3Llz9cgjj6igoKADNhkAAJguwp/irVu3+vydm5urmJgYlZWVafz48aqtrdVvfvMbrV+/Xrfeeqsk6Y033tCIESO0c+dOjRs3Tu+//76+/PJLffDBB4qNjdW1116rp59+WgsXLlR2drYiIyO1Zs0aJSYmavny5ZKkESNG6OOPP9aKFSvkcrk6aNMBAN3RvuEjNOLP+wLdBi7SRR0DU1tbK0mKjo6WJJWVlenUqVNKS0uzaoYPH67BgwertLRUklRaWqrk5GTFxsZaNS6XSx6PR3v37rVqzlxHc03zOlpSX18vj8fjMwEAgNDU7gDT1NSkuXPn6sYbb9TIkSMlSW63W5GRkerfv79PbWxsrNxut1VzZnhpXt687Hw1Ho9HJ06caLGfnJwcRUVFWVNCQkJ7Nw0AAAS5dgeYjIwM7dmzRxs2bOjIftotKytLtbW11lRVVRXolgAAQCfx6xiYZnPmzFFeXp62b9+uQYMGWfMdDocaGhp09OhRn1GY6upqORwOq2bXrl0+62s+S+nMmrPPXKqurpbdblfv3r1b7Mlms8lms7VncwAAgGH8GoHxer2aM2eONm3apOLiYiUmJvosT01NVc+ePVVUVGTN279/vyorK+V0OiVJTqdTFRUVqqmpsWoKCwtlt9uVlJRk1Zy5juaa5nUARsmOCnQHABBy/BqBycjI0Pr16/WHP/xB/fr1s45ZiYqKUu/evRUVFaWZM2cqMzNT0dHRstvtevzxx+V0OjVu3DhJ0qRJk5SUlKQHH3xQy5Ytk9vt1qJFi5SRkWGNoMyaNUsvv/yyFixYoIcffljFxcXauHGj8vPzO3jzAQCAifwagVm9erVqa2s1YcIExcXFWdObb75p1axYsUJ33HGHpkyZovHjx8vhcOjtt9+2loeHhysvL0/h4eFyOp164IEHNH36dC1dutSqSUxMVH5+vgoLCzVq1CgtX75cr732GqdQAwAASX6OwHi93gvW9OrVS6tWrdKqVatarRkyZIjee++9865nwoQJ+vzzz/1pDwAAdBP8FhIQYKtmFQe6BQAwDgEGAAAYhwADAACMQ4ABAOA89g0fEegW0AICDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADXf5kfqBbAADALwQYAABgHAIMAADtwI88BhYBBgAAGIcAAwDAD5ZPvSPQLaCNCDBAsMmOCnQHABD0CDAAAMA4BBgAAGAcAgwAADAOAQYAYDaOG+uWCDAAAMA4BBgAAGAcAgy6neS1yYFuAQBwkQgwAADAOAQYGIOREwDoOKZfdZgAgw7HD5wBADobAQYAABiHAAMAAIzjd4DZvn277rzzTsXHxyssLEzvvPOOz/J///d/V1hYmM902223+dR89913mjZtmux2u/r376+ZM2fq+PHjPjVffPGFbr75ZvXq1UsJCQlatmyZ/1sHAABCkt8Bpq6uTqNGjdKqVatarbntttt05MgRa/qf//kfn+XTpk3T3r17VVhYqLy8PG3fvl2PPfaYtdzj8WjSpEkaMmSIysrK9Nxzzyk7O1uvvvqqv+0CAIAQFOHvDSZPnqzJkyeft8Zms8nhcLS4bN++fdq6dat2796tMWPGSJJeeukl3X777frVr36l+Ph4rVu3Tg0NDXr99dcVGRmpa665RuXl5Xr++ed9gg4AAOieOuUYmG3btikmJkbDhg3T7Nmz9be//c1aVlpaqv79+1vhRZLS0tLUo0cPffLJJ1bN+PHjFRkZadW4XC7t379f33//fYv3WV9fL4/H4zMBAIDQ1OEB5rbbbtNvf/tbFRUV6b/+679UUlKiyZMnq7GxUZLkdrsVExPjc5uIiAhFR0fL7XZbNbGxsT41zX8315wtJydHUVFR1pSQkNDRmwYAAIJEhweYe++9Vz/5yU+UnJysu+++W3l5edq9e7e2bdvW0XflIysrS7W1tdZUVVXVqfcHAGg/x4flgW4hOPBL2u3W6adRX3HFFRo4cKAOHDggSXI4HKqpqfGpOX36tL777jvruBmHw6Hq6mqfmua/Wzu2xmazyW63+0wAACA0dXqA+eabb/S3v/1NcXFxkiSn06mjR4+qrKzMqikuLlZTU5PGjh1r1Wzfvl2nTp2yagoLCzVs2DBdeumlnd0yAAAIcn4HmOPHj6u8vFzl5eWSpEOHDqm8vFyVlZU6fvy45s+fr507d+rrr79WUVGR7rrrLg0dOlQul0uSNGLECN1222169NFHtWvXLv3xj3/UnDlzdO+99yo+Pl6SdP/99ysyMlIzZ87U3r179eabb2rlypXKzMzsuC0HAADG8jvAfPrpp7ruuut03XXXSZIyMzN13XXXafHixQoPD9cXX3yhn/zkJ7r66qs1c+ZMpaam6qOPPpLNZrPWsW7dOg0fPlwTJ07U7bffrptuusnnGi9RUVF6//33dejQIaWmpuoXv/iFFi9ezCnUAABAUjuuAzNhwgR5vd5WlxcUFFxwHdHR0Vq/fv15a1JSUvTRRx/52x4AAOgG+C0kAABgHAIMAKBbu/zJ/EC3gHYgwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDAAAMA4BphvhSHsAQKggwMBY/JotAHRfBBgAAPzAaHZwIMCgRUXFVwa6BQAAWkWAAQB0qFWzigPdAroBAgwAADAOAQYAABiHAAMAAIxDgAEAAMYhwAAAAOMQYAAAgHEIMAAAwDgEGAAAYBwCDBDiuKiYYbKjAt0BYAQCDBAiCCoAuhMCDAAAMA4BBgAAGIcAA/jJ8WF5oFsAgG6PAAOEgH3DRwS6BQDoUgQYAABgHAIM0EbLp94R2AY4vRYALAQYhKzktcmBbgEA0EkIMAAAwDgEmA5QVHxloFvAD7KzswPdAgCgC/gdYLZv364777xT8fHxCgsL0zvvvOOz3Ov1avHixYqLi1Pv3r2Vlpamr776yqfmu+++07Rp02S329W/f3/NnDlTx48f96n54osvdPPNN6tXr15KSEjQsmXL/N86AAAQkvwOMHV1dRo1apRWrVrV4vJly5bpxRdf1Jo1a/TJJ5/okksukcvl0smTJ62aadOmae/evSosLFReXp62b9+uxx57zFru8Xg0adIkDRkyRGVlZXruueeUnZ2tV199tR2bCISmlkb+vnnyowB0AgBdL8LfG0yePFmTJ09ucZnX69ULL7ygRYsW6a677pIk/fa3v1VsbKzeeecd3Xvvvdq3b5+2bt2q3bt3a8yYMZKkl156Sbfffrt+9atfKT4+XuvWrVNDQ4Nef/11RUZG6pprrlF5ebmef/55n6AD4FzZ2dla86O75b7l2kC3gm6iqPhKTbz1YKDbQDfTocfAHDp0SG63W2lpada8qKgojR07VqWlpZKk0tJS9e/f3wovkpSWlqYePXrok08+sWrGjx+vyMhIq8blcmn//v36/vvvO7JlAAA6FBeW7BodGmDcbrckKTY21md+bGystcztdismJsZneUREhKKjo31qWlrHmfdxtvr6enk8Hp8JAEIe1wdCNxUyZyHl5OQoKirKmhISEgLdEgAA6CQdGmAcDockqbq62md+dXW1tczhcKimpsZn+enTp/Xdd9/51LS0jjPv42xZWVmqra21pqqqqovfIAAAEJQ6NMAkJibK4XCoqKjImufxePTJJ5/I6XRKkpxOp44ePaqysjKrpri4WE1NTRo7dqxVs337dp06dcqqKSws1LBhw3TppZe2eN82m012u91nQmjg15+B7oP/72grvwPM8ePHVV5ervLyckn/OHC3vLxclZWVCgsL09y5c/Wf//mfevfdd1VRUaHp06crPj5ed999tyRpxIgRuu222/Too49q165d+uMf/6g5c+bo3nvvVXx8vCTp/vvvV2RkpGbOnKm9e/fqzTff1MqVK5WZmdlhGw4AAMzl92nUn376qW655Rbr7+ZQMWPGDOXm5mrBggWqq6vTY489pqNHj+qmm27S1q1b1atXL+s269at05w5czRx4kT16NFDU6ZM0Ysvvmgtj4qK0vvvv6+MjAylpqZq4MCBWrx4MadQA+j2Vs0qVsaaWwPdBhBwfgeYCRMmyOv1tro8LCxMS5cu1dKlS1utiY6O1vr16897PykpKfroIy7KBQBdJXltsipmVHT5/Z4TyrKjpOzaLu8DZgmZs5AAk3EFXQDwDwEGAAAYhwADAMAFLJ96R6BbwFkIMAAAwDgEGCBUcYl5ACGMAAMAAIxDgAF+kLw2OdAttKio+MpAtwAAQYcAg26PS5cDgHkIMAAAwDgEGAAAYBwCTHtwdgcA+GBXLLoaAQYAABiHAAMAQAgL1asIE2AAAIBxCDAAAMA4BJggFqrDfgAAXCwCDAAA7cQXzcAhwAAAAOMQYACDce0NAN0VAQbG+ebJj9pcu2pWcSd2AgBtxAVQOxwBBgAAGIcAAwBoF0Y4EUgEGAABtW/4iEC3gADi+Ud7EWCAs3BaZBcy+LiA5LXJrS7jQ/kfioqvDHQLCGEEGKCT8OYNdJ3zBcpQ17zt/nz5CoWQTYABAADGIcAAOK9Q+KYGIPQQYNBhLn8yP9AtdJjs7OxAtxDyQun1grbhrCV0JAJMN8aHNADAVAQYdEutfRPkG+I/MUICIJgRYAAENX9+OgJA90GAAc6DUQgACE4dHmCys7MVFhbmMw0fPtxafvLkSWVkZGjAgAHq27evpkyZourqap91VFZWKj09XX369FFMTIzmz5+v06dPd3SrAADAUJ0yAnPNNdfoyJEj1vTxxx9by+bNm6fNmzfrrbfeUklJiQ4fPqx77rnHWt7Y2Kj09HQ1NDRox44dWrt2rXJzc7V48eLOaBVAiOrOFzYDuoNOCTARERFyOBzWNHDgQElSbW2tfvOb3+j555/XrbfeqtTUVL3xxhvasWOHdu7cKUl6//339eWXX+p3v/udrr32Wk2ePFlPP/20Vq1apYaGhs5oFxeBy+53X6F2fRgCD7orU68a3ikB5quvvlJ8fLyuuOIKTZs2TZWVlZKksrIynTp1SmlpaVbt8OHDNXjwYJWWlkqSSktLlZycrNjYWKvG5XLJ4/Fo7969rd5nfX29PB6PzwRcDMeH5YFuAQDQig4PMGPHjlVubq62bt2q1atX69ChQ7r55pt17Ngxud1uRUZGqn///j63iY2NldvtliS53W6f8NK8vHlZa3JychQVFWVNCQkJHbthnczfMy04M+NcPCboKsF4cDeXADADo9Ydp8MDzOTJk/Wzn/1MKSkpcrlceu+993T06FFt3Lixo+/KR1ZWlmpra62pqqqqU++vRQb/su6F8J8OgdAZr7vO2FXERSF/0MHvgecLZXxhQaefRt2/f39dffXVOnDggBwOhxoaGnT06FGfmurqajkcDkmSw+E456yk5r+ba1pis9lkt9t9JgCB488HDAEZgL86PcAcP35cBw8eVFxcnFJTU9WzZ08VFRVZy/fv36/Kyko5nU5JktPpVEVFhWpqaqyawsJC2e12JSUldXa7wDkCcXBnqB0g21amHUzYXZ8nIBh0eID55S9/qZKSEn399dfasWOH/u3f/k3h4eG67777FBUVpZkzZyozM1MffvihysrK9NBDD8npdGrcuHGSpEmTJikpKUkPPvig/vSnP6mgoECLFi1SRkaGbDZbR7cLdCmGvRFs2P0FU3V4gPnmm2903333adiwYfr5z3+uAQMGaOfOnbrsssskSStWrNAdd9yhKVOmaPz48XI4HHr77bet24eHhysvL0/h4eFyOp164IEHNH36dC1durSjWwWAbuXsM+vYdecfvoAEl4iOXuGGDRvOu7xXr15atWqVVq1a1WrNkCFD9N5773V0a0Hhmyc/0qBnbw50G0CXufzJfH39bLrPvH/sKnrxvLfbN3yENMqsXUoAug6/hYRuw8TrunTHb3zBeIoyEKpM3oVIgAHQLbH7BDAbAQYIlBC+bhDQHUcP0bUIMADQAQJ5CviFTvU3fbTJtNPrW8Np9x2LAAMAZwiGD/u2XHvI5GMXQk1XjDZxbNi5CDCAeHMIBqGyy4FftfYDu1FxEQgw8EuoDOUC3VVzWOfHH7sOX5A6BwEGQJcKlZEWkzFK1Ik6cVTJ3+ct1J9nAkyAkMgBwE/scsIZCDDtxNHkLQuaxH/WGx0HPKKjsBs1MEy8ECU6FwEGANqgtbOT/J0PoGMQYIAACoWRvLOPaQmFbQIQ/AgwnaT5Tb27H+vCcDsAoDMQYAAghHC8F7oLAgzQBlwzA+hc/pxez/9HSAQYGIpvmf7h2iswAbucu0bQnC16kQgw3RynJgKhw5SgSlAxRzAfx0mAQZfprLNTQuXbhIk4VRhdjbPczu98o9OhFhwJMOhSfOChs3XUqGIwvdkzUgqciwBjGBO/fVz+ZD6jJBep+QPMxOc/lATi2KuLvc+2HvAazLsKQlEwBWRTEWAQEjgrIbiYOtJGQERH6spjks58D+wuI3YEGKCLne+bV7C+8ZgaSID2MOVg6O6OANNB2jv8Guzf+Nj1AwSvYA28+CeTdhWZ9n5PgOkiwR5U/BGQfeVn/bo00Bat7VpklyNgPgIM2i2UQllbcQG9HwRhoGQ3F7qjrvxCGWz/xwgwQcQaamzhw6GrXqTB9gJF8PHntWjC8LkJPUoKytAYDNiNFhjBcNYaAaabMW0fJ9CRguFNF23THUd44R8CDLpcd90NE8rHXRgzihGkOOuldTw2Hau1EG9iuCfAGCgYdvNc7EhOd/nAY3g7ePjzXHTXkI0WGLrrriMCSfP7dPLa5KAcESPAmMTQ/0gwS2sf3nwTvjATv8XCP8Hw5asrvsSaEOIJMAYIhv8w52PCC73ZmR8wwTCSdaZgep6DqZdQ1xm7FptHmzjm7Vyh9Jh09xFeAkyQ8fcMj674xheMQ4cIUowSdqjWRr0YDQsCvNYDLqgDzKpVq3T55ZerV69eGjt2rHbt2hXols7BG0nrTBqZMQ2vu5a19zVnyq6fixk9aOtjE8oHm6Ntgm10ujVBG2DefPNNZWZmasmSJfrss880atQouVwu1dTUBLq1jvNDgg+GF0tHD6sGwzY1O9+HfaiHrKAZLg/gt9Vgei1eSMjuEjBwtKKrRrg7W2cE0mDZxRy0Aeb555/Xo48+qoceekhJSUlas2aN+vTpo9dffz3QrZ3XvuEjzn3DbMd/XtN227TnBd1Zbw4h+yHwg2D9htyW59OkMCGZMzITCG19jwr1/48InIhAN9CShoYGlZWVKSsry5rXo0cPpaWlqbS0tMXb1NfXq76+3vq7trZWkuTxeDq+wXqvjjc2yuPx6Fh9nerqmtRU/3d5wv4x/+SpUzpWXyePx+Mz///d49I9Q+adM7+5vqX17Ju3VXW3trx+qz7LLmV9c8G2m+r/rsYTjdZjUl9fr6a64z7zT546JY/Ho7q6Jg2e95b6Dmu07rN5fnN98/z6+vp2z2/L89NUd1yeeq/V47H6OtWH/aN3T5ZdjUMG6URDnY7V9/zn/B/qz57f3MuJhjrV/9BLe+a3pe+6uiY1hf2jF3k8Vi91dU2KyftYB354HZ05v7n+eGOjfvXwZqVHnTu/tfq2PAZt6fvs5+fM19y7mxPVVL+sTa/ds+fvv+pqnUxObFv9Wffblr5PnvX8nPm8eTyeFp/PrKwsOf/1wq/R/aljdDI50e/Xelv6bn5+srKy1HRjeuuv9VZe063OP+sxON9rOibvY/U6Y35b+m5+zVnvC6281v157fo7v/l5PfMxu5Dm58fj8ai+vv6f78dnveba8po+3/zzfT40v697PB7ph8fsQlp6n/bnvaut79/N62/tNX3m/5lO+XzVPz+3vV7v+Qu9Qeivf/2rV5J3x44dPvPnz5/vveGGG1q8zZIlS7ySmJiYmJiYmEJgqqqqOm9WCMoRmPbIyspSZmam9XdTU5O+++47DRgwQGFhYe1er8fjUUJCgqqqqmS32zui1ZDDY3RhPEYXxmPUNjxOF8ZjdGHB/Bh5vV4dO3ZM8fHx560LygAzcOBAhYeHq7q62md+dXW1HA5Hi7ex2Wyy2Ww+8/r3799hPdnt9qB7koMNj9GF8RhdGI9R2/A4XRiP0YUF62MUFRV1wZqgPIg3MjJSqampKioqsuY1NTWpqKhITqczgJ0BAIBgEJQjMJKUmZmpGTNmaMyYMbrhhhv0wgsvqK6uTg899FCgWwMAAAEWtAFm6tSp+vbbb7V48WK53W5de+212rp1q2JjY7u0D5vNpiVLlpyzewr/xGN0YTxGF8Zj1DY8ThfGY3RhofAYhXm9FzpPCQAAILgE5TEwAAAA50OAAQAAxiHAAAAA4xBgAACAcQgw57Fq1Spdfvnl6tWrl8aOHatdu3YFuqWgsn37dt15552Kj49XWFiY3nnnnUC3FHRycnJ0/fXXq1+/foqJidHdd9+t/fv3B7qtoLJ69WqlpKRYF9RyOp3asmVLoNsKas8++6zCwsI0d+7cQLcSVLKzsxUWFuYzDR8+PNBtBZ2//vWveuCBBzRgwAD17t1bycnJ+vTTTwPdlt8IMK148803lZmZqSVLluizzz7TqFGj5HK5VFNTE+jWgkZdXZ1GjRqlVatWBbqVoFVSUqKMjAzt3LlThYWFOnXqlCZNmqS6urpAtxY0Bg0apGeffVZlZWX69NNPdeutt+quu+7S3r17A91aUNq9e7d+/etfKyUlJdCtBKVrrrlGR44csaaPP/440C0Fle+//1433nijevbsqS1btujLL7/U8uXLdemllwa6Nf91zM8vhp4bbrjBm5GRYf3d2NjojY+P9+bk5ASwq+Alybtp06ZAtxH0ampqvJK8JSUlgW4lqF166aXe1157LdBtBJ1jx455r7rqKm9hYaH3Rz/6kfeJJ54IdEtBZcmSJd5Ro0YFuo2gtnDhQu9NN90U6DY6BCMwLWhoaFBZWZnS0tKseT169FBaWppKS0sD2BlMV1tbK0mKjo4OcCfBqbGxURs2bFBdXR0/G9KCjIwMpaen+7w3wddXX32l+Ph4XXHFFZo2bZoqKysD3VJQeffddzVmzBj97Gc/U0xMjK677jr993//d6DbahcCTAv+7//+T42Njedc9Tc2NlZutztAXcF0TU1Nmjt3rm688UaNHDky0O0ElYqKCvXt21c2m02zZs3Spk2blJSUFOi2gsqGDRv02WefKScnJ9CtBK2xY8cqNzdXW7du1erVq3Xo0CHdfPPNOnbsWKBbCxp/+ctftHr1al111VUqKCjQ7Nmz9R//8R9au3ZtoFvzW9D+lAAQajIyMrRnzx72ybdg2LBhKi8vV21trX7/+99rxowZKikpIcT8oKqqSk888YQKCwvVq1evQLcTtCZPnmz9OyUlRWPHjtWQIUO0ceNGzZw5M4CdBY+mpiaNGTNGzzzzjCTpuuuu0549e7RmzRrNmDEjwN35hxGYFgwcOFDh4eGqrq72mV9dXS2HwxGgrmCyOXPmKC8vTx9++KEGDRoU6HaCTmRkpIYOHarU1FTl5ORo1KhRWrlyZaDbChplZWWqqanR6NGjFRERoYiICJWUlOjFF19URESEGhsbA91iUOrfv7+uvvpqHThwINCtBI24uLhzvhiMGDHCyF1tBJgWREZGKjU1VUVFRda8pqYmFRUVsV8efvF6vZozZ442bdqk4uJiJSYmBrolIzQ1Nam+vj7QbQSNiRMnqqKiQuXl5dY0ZswYTZs2TeXl5QoPDw90i0Hp+PHjOnjwoOLi4gLdStC48cYbz7mUw//+7/9qyJAhAeqo/diF1IrMzEzNmDFDY8aM0Q033KAXXnhBdXV1euihhwLdWtA4fvy4zzebQ4cOqby8XNHR0Ro8eHAAOwseGRkZWr9+vf7whz+oX79+1jFUUVFR6t27d4C7Cw5ZWVmaPHmyBg8erGPHjmn9+vXatm2bCgoKAt1a0OjXr985x01dcsklGjBgAMdTneGXv/yl7rzzTg0ZMkSHDx/WkiVLFB4ervvuuy/QrQWNefPm6V//9V/1zDPP6Oc//7l27dqlV199Va+++mqgW/NfoE+DCmYvvfSSd/Dgwd7IyEjvDTfc4N25c2egWwoqH374oVfSOdOMGTMC3VrQaOnxkeR94403At1a0Hj44Ye9Q4YM8UZGRnovu+wy78SJE73vv/9+oNsKepxGfa6pU6d64+LivJGRkd5/+Zd/8U6dOtV74MCBQLcVdDZv3uwdOXKk12azeYcPH+599dVXA91Su4R5vV5vgLITAABAu3AMDAAAMA4BBgAAGIcAAwAAjEOAAQAAxiHAAAAA4xBgAACAcQgwAADAOAQYAABgHAIMAAAwDgEGAAAYhwADAACMQ4ABAADG+f94uYmdvXmjDQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 \n",
    "print(\"similar to above, but for angles\")  #convention is angle[a][b] is from a to b\n",
    "uuAngle = [[0. for t in range(nHDs)] for t in range(nHDs)]\n",
    "\n",
    "pi = 3.141592653\n",
    "twoPi = pi*2.\n",
    "startTime = time.time()\n",
    "for i, t in enumerate(populatedTractList):\n",
    "    if i %200 == 0:\n",
    "        print(\"working on unit-unit angles for unit\",t,\"out of\",nHDs,\". Time =\",int(time.time() - startTime)  )\n",
    "    for tt in populatedTractList:\n",
    "        if tt > t and (HDcountyNo[tt] in closeCountyList[HDcountyNo[t]] or HDcountyNo[t] == HDcountyNo[tt]):  #time-saver; do the triangle matrix\n",
    "            angLE = math.atan2(hdCP[tt].y - hdCP[t].y, xScale * (hdCP[tt].x - hdCP[t].x) )\n",
    "            uuAngle[t][tt], uuAngle[tt][t] = angLE % twoPi, (angLE + pi) % twoPi\n",
    "print(\"All done with angles; total elapsed seconds =\",int(time.time()-startTime) )\n",
    "plt.hist(uuAngle)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4cc54eba-ca37-4680-9699-37332133afb8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "713311.75 8 5706494.0 8.0 5706494.0\n",
      "5706494.0 5706494 1.0\n"
     ]
    }
   ],
   "source": [
    "print(r3(aDP), nDistricts, statePop, statePop/aDP, trueStatePop)\n",
    "HDweight = [0 for t in range(nHDs)]\n",
    "for t in populatedTractList:\n",
    "    HDweight[t] = tractPop[t] / trueStatePop #skipping the cutList tracts\n",
    "print(statePop,np.sum([tractPop[t] for t in populatedTractList]), np.sum(HDweight)) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "dac2348a-060a-40a9-beeb-02ff70ec1aa1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\n"
     ]
    }
   ],
   "source": [
    "print(\"for extended peninsulas, need to broaden the 'neighborCountyList' to include all co-squished counties' neighbors\")\n",
    "opt2nbrCtyList = [neighborCountyList[c].copy() for c in range(nCounties)]\n",
    "for i in range(nClips):\n",
    "    cList = toSquishCountiesList[i]\n",
    "    for c in cList:\n",
    "        for cc in cList:\n",
    "            for ccc in neighborCountyList[cc]:\n",
    "                if ccc not in opt2nbrCtyList[c] and ccc != c:\n",
    "                    opt2nbrCtyList[c].append(ccc)\n",
    "#for c in range(nCounties):\n",
    "#    for cc in opt2nbrCtyList[c]:\n",
    "#        plotPoly(countyGeom[cc])\n",
    "#    plotCenter(c,countyGeom[c])\n",
    "#    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "3873aaa2-0c39-4ac0-99c3-92dd7c18c555",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\n",
      "For each Home District, we will consider a wedge as one-from-full when it is within 1111.835 of targetWedgePop\n",
      "I am working on HD number 0 of 4110 HDs.  Elapsed sec = 0\n",
      "I am working on HD number 401 of 4110 HDs.  Elapsed sec = 134\n",
      "I am working on HD number 801 of 4110 HDs.  Elapsed sec = 246\n",
      "I am working on HD number 1201 of 4110 HDs.  Elapsed sec = 373\n",
      "I am working on HD number 1601 of 4110 HDs.  Elapsed sec = 517\n",
      "I am working on HD number 2003 of 4110 HDs.  Elapsed sec = 634\n",
      "I am working on HD number 2403 of 4110 HDs.  Elapsed sec = 757\n",
      "I am working on HD number 2803 of 4110 HDs.  Elapsed sec = 877\n",
      "I am working on HD number 3203 of 4110 HDs.  Elapsed sec = 985\n",
      "I am working on HD number 3603 of 4110 HDs.  Elapsed sec = 1075\n",
      "I am working on HD number 4004 of 4110 HDs.  Elapsed sec = 1185\n",
      "1224.102 seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of unit usage.\n",
      "unit avg and sd usage are 1.00067 0.1521\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#continuing option 2 .......\n",
    "# BELOW modified Dec23 to use inter-unit distances and angles, (counties still wedgeIntersxn) otherwise similar to HD2\n",
    "# --THIS ESSENTIALLY TAKES THE ORIGINAL TRACT-BASED HD centerpoints, and redraws HD2 districts after convexifying corners and convex_hull\n",
    "print(\"Here is the main code to draw 4-wedge Home Districts for each populated HD centerpoint\") \n",
    "#this is a hybrid of HD2 and the organic code, in that all wedge tracts must be in a chain of neighboring counties\n",
    "#General sequence: draw 4 equi-angle wedges with random starting orientation.  If not all can fill a quarter aDP ...\n",
    "# ... find the closest map boundary point to the tract center point in the shortest wedge.  Orient the 0th wedge to face this point\n",
    "# ... determine the \"maxWedgePop\" for this short wedge and the other three wedges extended past the boundary\n",
    "# ...  if this results in only one short wedge, or opposing short wedges, adjust wedge angles\n",
    "# Regardless of whether we re-oriented or adjusted angles, compute each wedgePop for infinite radius\n",
    "#   ... then adjust other targetWedgePops if some found to be short.\n",
    "#   ... for non-shorted wedges, use bisection method to adjust radius to meet targetWedgePop\n",
    "#   ... once total HDpop within tolerance, add/subtract a tract fraction to fulfill HDpop\n",
    "#  create a list of fully used tracts per HD, save the tract# of the split tract and its fractional use\n",
    "#  Compute tractUse across all HDs at the end from the tractUsageLists.  Defer patching and partisan calcs to another code\n",
    "\n",
    "pi=3.1415926536\n",
    "#MAPhull = MAP.convex_hull #used for exitAngle calc.  Defined in an above block to allow user modification\n",
    "nWedges = 4  #number of wedges per home district polygon  \n",
    "avgWedgeAngle = 2.*pi / nWedges\n",
    "angle, angle2, wedgePoly = [0.]*nWedges, [0.]*nWedges, [dummyPoly]*nWedges  #start and stop angle of each wedge\n",
    "pt1, pt2, pt3 = [Point(0,0)]*nWedges, [Point(0,0)]*nWedges, [Point(0,0)]*nWedges #these four define the polygon wedge for a growing home district\n",
    "tractUse = [0.] * nHDs  #this will store how much we use this tract in ALL HD's vs. expectation\n",
    "HDtractList = [list()]*nHDs\n",
    "splitTractNo = [-999]*nHDs  #the tract that is only partially used to finish each HD\n",
    "splitTractUse = [0.]*nHDs  #and this is what fraction of the split tract is included\n",
    "HDvPop = [0.]*nHDs\n",
    "#HDweight = [tractPop[t] / (statePop - excludedPop) for t in range(nTracts)]  #relative weight of each drawn HD\n",
    "HDPoly1 = [dummyPoly]*nHDs  #final 4-wedge shape, unionized from blockgroups / tracts\n",
    "HDarea = [0.]*nHDs  #geographical area of each home district (after boundary trim)\n",
    "HDradius = [[0.]*nWedges for t in range(nHDs)] #final wedge length for each Home District wedge\n",
    "HDangle = [[0.]*nWedges for t in range(nHDs)] #final starting angle for each HD wedge\n",
    "angle0 = [-999.] * nHDs  #orientation of 0th wedge.  Random except re-oriented if we are near-boundary\n",
    "avgTractPop = statePop/len(populatedTractList)\n",
    "tolerPops = [0.8 * avgTractPop, 0.5 * np.max(tractPop)]  #threshold gap before adding one more unit to a wedge \n",
    "tolerPop = tolerPops[0]\n",
    "print(\"For each Home District, we will consider a wedge as one-from-full when it is within\",r3(tolerPops[0]),\"of targetWedgePop\")\n",
    "tractPrintInterval = 400  #for tracking progress\n",
    "levelL = 0.36 #sqrt(pop) for angle=std  These two control distortion in wedge angles relative to wedgePop shortness\n",
    "maxAngleRatio = 1.9  #for tightening tract weighting near boundaries  #HD2\n",
    "maxAngle = 1.8*pi/2. # limit to avoid wedges too close to half a pie\n",
    "minAdjRatio = 0.5  #min ratio of pop of adjacent wedge (to min wedge) to targetWedgePop to not consider this a corner HD\n",
    "maxUncap = 0.5 #the max ratio of uncaptured pop in a maxWedge vs. target wedge pop that we will not stretch to include (7/23)\n",
    "oppWt = 0.0    #the fraction of gap between normal targetWedgePop and the minWedgePop that we allow the opposite wedge to add to tgtPop = minWedgePop\n",
    "maxWedgePop = [0.] * nWedges  #wedge pop if we explode wedge to maximum radius\n",
    "printDebug = \"no\"\n",
    "codeStartTime = time.time()\n",
    "hdCPpop = [HDweight[t] * statePop for t in range(nHDs)]\n",
    "countyHDlist = [list() for c in range(nCounties)]\n",
    "for t in populatedTractList:\n",
    "    countyHDlist[HDcountyNo[t]].append(t)\n",
    "\n",
    "for kkkj, t in enumerate(populatedTractList):  #range(nTracts) : #loop on each tract. \n",
    "    hC = HDcountyNo[t]     #this tract's home county\n",
    "    HDtractList[t] = [t] #seed the list of tracts in this HD\n",
    "    wedgeList = [list() for w in range(nWedges)]   #list of each wedge's tracts, excluding home tract\n",
    "    barredList = list()  #list of wedge numbers for which we are barred from altering their targetWedgePops\n",
    "    if (kkkj % tractPrintInterval) == 0 : \n",
    "        print(\"I am working on HD number {0} of {1} HDs.  Elapsed sec = {2}\".format(t,nHDs,int(time.time()-codeStartTime) ) )  \n",
    "    nActiveWedges = nWedges #active wedges have not run over boundary\n",
    "    wedgePop = [0.]*nWedges\n",
    "    targetWedgePop = [aDP / nWedges]*nWedges  #at beginning, split districtPop equally among wedges\n",
    "    \n",
    "    angle0[t] = random.uniform(0,2.*pi)  #imparts random orientation to the midangle of our starting wedge\n",
    "    wedgeAngle = [avgWedgeAngle for w in range(nWedges) ] #reset to equi-angle when starting each tract\n",
    "    for nW in range(nWedges-1):\n",
    "        wedgeAngle[nW] += random.uniform(-0.0001,0.0001)  #this wiggle solves a later indexing ambiguity for corner tracts\n",
    "    wedgeAngle[nWedges-1] = 2.*pi - (np.sum(wedgeAngle) - wedgeAngle[nWedges-1] ) #squaring up to 2pi total\n",
    "    startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "    for nW in range(1,nWedges):\n",
    "        startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "    endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "    #  TRIAL LOOP TO SEE WHICH WEDGES CAN FILL TO TARGET POP w/equiangle wedges\n",
    "    maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]    \n",
    "    maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "    willFill = [0] * nWedges #would this wedge meet its target with infinite radius?\n",
    "    for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "        iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "        #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList) \n",
    "        nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "        maxWedgePop[nW] += (iCP + nonCP)\n",
    "        wedgeList[nW] = Li + Ln\n",
    "        if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "            willFill[nW] = 1\n",
    "     \n",
    "    if np.sum(willFill) < nWedges:  #at least one wedge couldn't reach its wedgePop target (went over boundary) ...\n",
    "        minW = maxWedgePop.index(np.min(maxWedgePop)) #.. so we will orient the 0th wedge to face the shortest wedgePop's closest boundary\n",
    "        exitAngle = getExitAngle(hdCP[t],maxWedgePoly[minW], MAPhull, startAngle[minW], endAngle[minW])\n",
    "        angle0[t] = exitAngle - 0.5*(2.*pi / nWedges)  #Now reset all angles based on new starting orientation.  All wedge angles still equal\n",
    "        startAngle = [angle0[t] for nW in range(nWedges)]\n",
    "        for nW in range(1,nWedges):\n",
    "            startAngle[nW] = startAngle[nW-1] + wedgeAngle[nW-1]\n",
    "        endAngle = [startAngle[nW] + wedgeAngle[nW] for nW in range(nWedges)]\n",
    "        maxWedgePoly = [buildWedge(hdCP[t],startAngle[nW],endAngle[nW], maxD, xScale) for nW in range(nWedges) ]\n",
    "        \n",
    "        willFill = [0]*nWedges\n",
    "        #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation (wedge angles still constant)\n",
    "        maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop        \n",
    "        for nW in range(nWedges):   #... then add in-county and nonCounty wedge Pop from contiguous chain of counties\n",
    "            iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])\n",
    "            #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "            nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                    opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "            maxWedgePop[nW] += (iCP + nonCP)\n",
    "            wedgeList[nW] = Li + Ln\n",
    "            if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                willFill[nW] = 1       \n",
    "    \n",
    "    if np.sum(willFill) < nWedges:  #check if we need to modify wedge angles after possible re-orientation.  \n",
    "        # If so, re-draw maxWedgePoly's, re-calc maxWedgePops\n",
    "        nUnfilledWedges = nWedges - np.sum(willFill)\n",
    "        isChange, newInclA = getNewAngles(maxWedgePop, targetWedgePop, aDP, levelL, minAdjRatio, maxAngle, maxAngleRatio, nUnfilledWedges )\n",
    "        if isChange: #no longer equi-angle\n",
    "            newStartAngle = [0.5*(startAngle[nW]+endAngle[nW]) - 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            newEndAngle =   [0.5*(startAngle[nW]+endAngle[nW]) + 0.5*newInclA[nW] for nW in range(nWedges) ]\n",
    "            startAngle, endAngle, wedgeAngle = newStartAngle.copy(), newEndAngle.copy(), newInclA.copy()\n",
    "            maxWedgePoly = [ buildWedge(hdCP[t],startAngle[nW],endAngle[nW], \n",
    "                                        maxD/math.cos(0.5*wedgeAngle[nW]), xScale ) for nW in range(nWedges) ]\n",
    "            willFill = [0]*nWedges\n",
    "            #Now re-calc each maxWedgePop if we extend wedge's radius past map with new angle0 orientation and new wedge angles\n",
    "            maxWedgePop =[ hdCPpop[t]*wedgeAngle[nW]/(2.*pi) for nW in range(nWedges) ]  #seed wedge with fraction of its home tract pop\n",
    "            for nW in range(nWedges):   #... then add in-county Pop and wedge Pop from contiguous chain of counties\n",
    "                iCP, Li   = getCountyWP(t,maxWedgePoly[nW], hdCP, hdCPpop, countyHDlist[hC])                \n",
    "                #nonCP, Ln = getNonCWP(maxWedgePoly[nW], hC, tractCP, tractPop, countyGeom, countyPop, countyTractList, neighborCountyList)\n",
    "                nonCP, Ln = getNonCWP_c(startAngle[nW],endAngle[nW], hC, hdCP, hdCPpop, countyGeom, countyPop, countyHDlist,\n",
    "                                        opt2nbrCtyList, uuDist[t], uuAngle[t], maxWedgePoly[nW])\n",
    "                maxWedgePop[nW] += (iCP + nonCP)\n",
    "                wedgeList[nW] = Li + Ln\n",
    "            minW = wedgeAngle.index(np.max(wedgeAngle)) #should be 0th wedge, but playing it safe.  This is the 1st wide-angle wedge ..\n",
    "            oppW = int(int(minW+nWedges/2)%nWedges)   #and its opposite\n",
    "            if maxWedgePop[minW] > maxWedgePop[oppW] and maxWedgePop[oppW] < aDP / nWedges:  #minW and oppW are flipped after inclA adjmt\n",
    "                oppW = minW\n",
    "                minW = int(int(minW+nWedges/2)%nWedges)\n",
    "            if maxWedgePop[minW] < targetWedgePop[oppW]:  #we need to constrain oppW in this HD2 implementation; redistribute tgt to adjacents\n",
    "                maxNonOppW = np.sum(maxWedgePop) - maxWedgePop[oppW] #...but only if other wedges can pick up slack; need to check\n",
    "                minOppWedgePop = aDP - maxNonOppW  #cannot set oppW target below this or we won't reach aDP across all wedges\n",
    "                barredList = [oppW]\n",
    "                targetWedgePop[oppW] = max(minOppWedgePop, maxWedgePop[minW] + oppWt * (targetWedgePop[oppW] - maxWedgePop[minW]) )\n",
    "                tWPgap = aDP / float(nWedges) - targetWedgePop[oppW] \n",
    "                for nW in range(nWedges):\n",
    "                    if nW != minW and nW != oppW:\n",
    "                        targetWedgePop[nW] += tWPgap/float(nWedges - 2.)  #if oppW target is limited, allot to adjacent wedges\n",
    "            for nW in range(nWedges):\n",
    "                if maxWedgePop[nW] > targetWedgePop[nW]:\n",
    "                    willFill[nW] = 1  \n",
    "    \n",
    "    if abs(np.sum(targetWedgePop) / aDP - 1.) > 0.001:\n",
    "        raise Exception(\"FAIL! Our target wedgepops\",targetWedgePop, np.sum(targetWedgePop),\"no longer add up to\",aDP)\n",
    "    \n",
    "    if np.sum(willFill) == nWedges:  #all wedges will fill.  Will any leave a small near-boundary remnant?  If so, pick up smallest remnant\n",
    "        remnantWedgePopFrac = [ ( maxWedgePop[w] - targetWedgePop[w] )/targetWedgePop[w] for w in range(nWedges) ]\n",
    "        if np.min(remnantWedgePopFrac) < maxUncap :  #lessen tWP's of *adjacent* wedges, then increase this wedge's target --> max\n",
    "            minW = remnantWedgePopFrac.index(np.min(remnantWedgePopFrac))\n",
    "            oppW = int((minW+nWedges/2)%nWedges)\n",
    "            #print(\"filling to boundary for tract,wedge, tWP, mWP =\",t,minW, r3(targetWedgePop[minW]), maxWedgePop[minW])\n",
    "            for nW in range(nWedges):\n",
    "                if nW != minW and nW != oppW:\n",
    "                    targetWedgePop[nW] -= (remnantWedgePopFrac[minW] * targetWedgePop[minW] ) / (nWedges - 2.)\n",
    "            targetWedgePop[minW] = maxWedgePop[minW]\n",
    "            #       OK, READY TO SOLVE FOR NON-FILLED WEDGE SIZES once we adjust targets for unfilled wedges\n",
    "    #print(t,\" prior to rebalanceTWP call, mWPs, tWPs are\",maxWedgePop, targetWedgePop)\n",
    "    targetWedgePop, willFill = rebalanceTWPs(maxWedgePop, targetWedgePop, barredList)\n",
    "    #if np.max(targetWedgePop) - np.min(targetWedgePop) > 0.02 * aDP: #debug\n",
    "    #    print(\"for tract\",t,\",  After rebalancing but before tweaks for blocky pop adds: willFill, targetWedgePops and maxWedgePops are ...\")\n",
    "    #    for w in range(nWedges):\n",
    "    #        print(w, willFill[w],r3(targetWedgePop[w]),int(maxWedgePop[w]) )\n",
    "    for w in range(nWedges):  #WHEW!  WE CAN FINALLY ASSIGN ALL WEDGES' POPS AND TRACTLISTS\n",
    "        loop = 0\n",
    "        if willFill[w] == 0:  #wedge is maxed out\n",
    "            wedgePop[w] = maxWedgePop[w]\n",
    "            #wedgeList[w] = ...  #we already captured this list = maxWedge list\n",
    "            HDradius[t][w] = maxD/math.cos(0.5*wedgeAngle[w])\n",
    "        else:  #need to solve for wedge radius to meet targetPop.  Use bisection as scipy minimize no faster\n",
    "            HDcpWP = hdCPpop[t] * wedgeAngle[w]/(2.*pi)\n",
    "            nonHDcpTWP = targetWedgePop[w] - HDcpWP\n",
    "            #wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeB(nontractTWP,t,hC,maxWedgePoly[w],tolerPop,tractCP, tractPop,\n",
    "            #                                                        countyNo,countyTractList,countyGeom, neighborCountyList,uuDist[t])\n",
    "            wedgePop[w], wedgeList[w], HDradius[t][w] = solveWedgeC(nonHDcpTWP,t,hC, maxWedgePoly[w],startAngle[w], endAngle[w], tolerPop,\n",
    "                                                                    hdCP, hdCPpop,HDcountyNo, countyHDlist,countyGeom,\n",
    "                                                                    opt2nbrCtyList,uuDist[t],uuAngle[t])\n",
    "            popGap = nonHDcpTWP - wedgePop[w]  #gap between target and solved wedge pop; can be negative\n",
    "            notYetAdjusted, nextW = True, w+1  #looking to adjust a later wedge's target pop to minimize drift in total HD pop\n",
    "            while notYetAdjusted and nextW < nWedges:\n",
    "                if willFill[nextW] == 1 and maxWedgePop[nextW] > targetWedgePop[nextW] + popGap :  #can accommodate\n",
    "                    targetWedgePop[nextW] += popGap\n",
    "                    notYetAdjusted = False\n",
    "                nextW +=1          \n",
    "\n",
    "        HDangle[t][w] = startAngle[w]\n",
    "    #print(t,\"tract. After TWP adjustment, targetWedgePops are\",targetWedgePop)\n",
    "    HDtractList[t] = [t]\n",
    "    totPop = hdCPpop[t]\n",
    "    for nW in range(nWedges):\n",
    "        for tt in wedgeList[nW]:\n",
    "            HDtractList[t].append(tt)  #building the list of tracts in the Home District  (we'll keep up with below changes)\n",
    "            totPop += hdCPpop[tt]\n",
    "    offsetPop = totPop - aDP  #we have solved for all wedge radii to get each within one tractPop of target ... \n",
    "    HDvPop[t] = totPop\n",
    "    #if offsetPop > 0:   #... now include a splitPoly to nail the avg District Pop\n",
    "    #    isOver = True  #we slightly overshot.  ID the farthest-away tract for split-jettison\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], hdCPpop, neighborList)\n",
    "    #    HDvPop[t] = totPop - (1. - splitTractUse[t]) * tractPop[splitTractNo[t]]\n",
    "    #if offsetPop < 0:\n",
    "    #    isOver = False  #we have undershot.  Pick up the nearest contiguous tract that can be split to fill the gap\n",
    "    #    splitTractNo[t], splitTractUse[t] = getPartialTract(t, HDtractList[t], offsetPop, uuDist[t], tractPop, neighborList)\n",
    "    #    HDtractList[t].append(splitTractNo[t])\n",
    "    #    HDvPop[t] = totPop + splitTractUse[t]*tractPop[splitTractNo[t]]       \n",
    "    #if abs(1. - HDvPop[t]/aDP) > 0.005 :  #something went wrong with pop assignation for this HD\n",
    "    #    print(\"WARNING! Total Home District pop was\",HDvPop[t],\"vs target\",aDP,\"for tract\",t)   ##### hdCP topology not yet known; skip partial\n",
    "        \n",
    "    HDPoly1[t] = dummyPoly  #tractGeom[t] #skip constructing the HD poly shape.  Do compute area of the Home District, including final partial\n",
    "    HDarea[t] = 0.\n",
    "    for tt in HDtractList[t]:\n",
    "        if tt == splitTractNo[t]:\n",
    "            tractUse[tt] += nDistricts * HDweight[t] * splitTractUse[t] \n",
    "            #HDarea[t]   += tractArea[tt] * splitTractUse[t]  #these are original (nonsquished) areas\n",
    "            \n",
    "        else:\n",
    "            tractUse[tt] += nDistricts * HDweight[t]\n",
    "            #HDarea[t]    += tractArea[tt]\n",
    "            #HDPoly1[t] = HDPoly1[t].union(tractGeom[tt])\n",
    "    HDPoly1[t] = buildPoly(hdCP[t],HDradius[t], HDangle[t] )\n",
    "    #HDarea[t] = HDPoly1[t].area + splitTractUse[t] * tractArea[splitTractNo[t]]  \n",
    "    #if splitTractUse[t] > 0.5:\n",
    "    #    HDPoly1[t] = HDPoly1[t].union(tractGeom[splitTractNo[t]])\n",
    "                          \n",
    "    #ALL DONE ESTABLISHING THE FINAL HDTRACTLIST.  FINALIZE STATS\n",
    "totalTime = time.time() - codeStartTime\n",
    "print(r3(totalTime),\"seconds elapsed. All done computing HD shapes and tractlists.  Here is a histogram of vtd usage.\")\n",
    "n_bins=50\n",
    "popTractUse, plotWts = [tractUse[t] for t in populatedTractList], [HDweight[t] for t in populatedTractList]\n",
    "\n",
    "origHDuseAvg, origHDuseSD = getWeightedAvgAndSD(tractUse,HDweight)\n",
    "print(\"vtd avg and sd usage are\",r5(origHDuseAvg), r5(origHDuseSD) )\n",
    "\n",
    "fig, ax = plt.subplots(tight_layout=True)\n",
    "ax.hist(popTractUse, bins=n_bins, weights=plotWts)\n",
    "plt.show()\n",
    "HDvPop = [np.sum([hdCPpop[tt] for tt in HDtractList[t]]) for t in range(nHDs)]\n",
    "plt.scatter([hdCPpop[t] for t in populatedTractList],[HDvPop[t] for t in populatedTractList] )\n",
    "print(\"here are your HD pops\")\n",
    "plt.show()\n",
    "origHDHDtractList = [HDtractList[t].copy() for t in range(nHDs)] #save for posterity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "37c238bb-b340-431b-ad11-95e4409d9699",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now we will write the polygon-based results to a file\n"
     ]
    }
   ],
   "source": [
    "#last block of option 2 (i.e. generating polygonal HDs from scratch)\n",
    "print(\"Now we will write the polygon-based results to a file\")\n",
    "tractNo = [t for t in range(nHDs) ]\n",
    "HDangle0 = [HDangle[t][0] for t in range(nHDs) ]\n",
    "HDangle1 = [HDangle[t][1] for t in range(nHDs) ]\n",
    "HDangle2 = [HDangle[t][2] for t in range(nHDs) ]\n",
    "HDangle3 = [HDangle[t][3] for t in range(nHDs) ]\n",
    "HDradius0 = [HDradius[t][0] for t in range(nHDs)]\n",
    "HDradius1 = [HDradius[t][1] for t in range(nHDs)]\n",
    "HDradius2 = [HDradius[t][2] for t in range(nHDs)]\n",
    "HDradius3 = [HDradius[t][3] for t in range(nHDs)]\n",
    "hdCPx, hdCPy =   [hdCP[t].x for t in range(nHDs)], [hdCP[t].y for t in range(nHDs)]\n",
    "\n",
    "\n",
    "paramList = [\"STATE\",\"statePop\",\"nDistricts\",\"nHDs\",\"nWedges\",\"popn-toler\",\"levelL\", \"maxAngleRatio\",\n",
    "             \"maxAngle\",\"minAdjRatio\",\"maxUncap\", \"oppWt\", \"calc sec\",\"xScale\",\"outputs...\"]\n",
    "paramValues = [STATE,statePop, nDistricts, nHDs, nWedges, tolerPop, levelL, maxAngleRatio, maxAngle, minAdjRatio, maxUncap,\n",
    "               oppWt, totalTime, xScale, -777]\n",
    "for i in range(nHDs-len(paramList)):\n",
    "    paramList.append(\".\")\n",
    "    paramValues.append(-99)  #so all columns have same number of entries, even the parameter list\n",
    "HDdf = pd.DataFrame( {\"paramList\": paramList,\"paramValues\":paramValues,\"countyNo\":HDcountyNo,\n",
    "                    \"tractNo\":tractNo,\"centroid x\":hdCPx,\"centroid y\":hdCPy,\"tractPop\":hdCPpop,\n",
    "                    \"HDweight\":HDweight,\"HD-pop\":HDvPop,\"HDarea\":HDarea,\n",
    "                    \"startAngle\":angle0,\"HDangle0\":HDangle0,\"HDangle1\":HDangle1,\"HDangle2\":HDangle2,\"HDangle3\":HDangle3,\n",
    "                    \"HDradius0\":HDradius0,\"HDradius1\":HDradius1,\"HDradius2\":HDradius2, \"HDradius3\":HDradius3,\"tractUse\":tractUse,\n",
    "                    \"splitTractNo\":splitTractNo,\"splitTractUse\":splitTractUse,\"HDtractList\":HDtractList} ) \n",
    "\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Bnopatch\"+str(int(nDistricts))+\"nW4.csv\"  #solveWedgeB\n",
    "outname = STATE+str(int(nHDs))+\"convexHD2_\"+str(int(nDistricts))+\"nW4_21Mar.csv\"  #solveWedgeC\n",
    "#outname = STATE+str(int(nTracts))+\"HD2Buutpatch\"+str(int(nDistricts))+\"nW4.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "HDdf.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "075013a3-f3ee-4a44-ac4a-27a7492e027a",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "6e7e8ccd-8e11-4d6d-970d-b059401e0a3b",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the original HD polygon shape assignment csv, e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv ./2024state_HD_output/MN4110convexHD2_8nW4_07Apr.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "I have read back in the original HD shapes\n",
      "County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\n",
      "I found 1 populd HDs whose centers fall outside vtd-based county lines.  Assign to closest county\n",
      "FYI, here are those manually assigned HDcenters to their counties\n",
      "3946 0.0001042671735044  is the HD row and its weight in the ensemble\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Ready to capture unit centroids based on these HD poly shapes; see next block\n"
     ]
    }
   ],
   "source": [
    "#OPTION 2 --> 1 - we already have an ensemble of HDpoly's and their weights (from running option 2 above)\n",
    "#read them in\n",
    "#determine each cluster's required area fraction capture to get 1.00 cluster use across the HD set\n",
    "#then determine total pop (including cluster in/out) for each HD, and total unit use\n",
    "#then move into triage\n",
    "infilename = input(\"enter the original HD polygon shape assignment csv, \"+ \n",
    "                   \"e.g. ./2024state_HD_output/FL7211convexHD2_26nW4_03Mar.csv or ./state_HD_output/AZ9HD1tol0.005nW425Mar.csv\")\n",
    "shapeDF = pd.read_csv(infilename)\n",
    "HDvPop = shapeDF[\"HD-pop\"].to_list()\n",
    "HDweight = shapeDF['HDweight'].to_list() #shapeDF['HDwt'].to_list() or #shapeDF['HDweight'].to_list()\n",
    "HDarea = shapeDF['HDarea'].to_list()\n",
    "#tractPop = shapeDF['tractPop'].to_list()   #we will use vtd-mapped pops instead\n",
    "nHDs = len(shapeDF)\n",
    "hdCPx = shapeDF['centroid x'].to_list()   #note: these may be translated from outcroppings into a convex representation of the map\n",
    "hdCPy = shapeDF['centroid y'].to_list()\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs) ]\n",
    "HDradius0 = shapeDF['HDradius0'].to_list()\n",
    "HDradius1 = shapeDF['HDradius1'].to_list()\n",
    "HDradius2 = shapeDF['HDradius2'].to_list()\n",
    "HDradius3 = shapeDF['HDradius3'].to_list()\n",
    "HDangle0 = shapeDF['HDangle0'].to_list()\n",
    "HDangle1 = shapeDF['HDangle1'].to_list()\n",
    "HDangle2 = shapeDF['HDangle2'].to_list()\n",
    "HDangle3 = shapeDF['HDangle3'].to_list()\n",
    "HDradius, HDangle = list(), list()\n",
    "for t in range(nHDs):\n",
    "    HDradius.append( [HDradius0[t],HDradius1[t],HDradius2[t],HDradius3[t] ] )\n",
    "    HDangle.append(  [HDangle0[t], HDangle1[t], HDangle2[t], HDangle3[t]  ] )\n",
    "print(\"I have read back in the original HD shapes\")\n",
    "popHDlist = list()\n",
    "HDpoly = [dummyPoly for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    if HDweight[t] > 0.000001:\n",
    "        popHDlist.append(t)\n",
    "        HDpoly[t] = buildArcPoly(hdCP[t],HDradius[t], HDangle[t], xScale)\n",
    "if \"pigs\" == \"can fly\": #countyNo in shapeDF.columns.values:\n",
    "    HDcountyNo = shapeDF['countyNo'].to_list()\n",
    "else:\n",
    "    print(\"County numbers not in input file. Now I will assign each HD center to a county based on the county geoms\")\n",
    "    HDcountyNo = [-999]*nHDs\n",
    "    for t in popHDlist:\n",
    "        for c, geom in enumerate(countyGeom):\n",
    "            if geom.contains(hdCP[t]):\n",
    "                HDcountyNo[t] = c\n",
    "                break\n",
    "    unassignedList = list()\n",
    "    for t in popHDlist:\n",
    "        if HDcountyNo[t] == -999:\n",
    "            unassignedList.append(t)\n",
    "    if len(unassignedList) > 0:\n",
    "        print(\"I found\",len(unassignedList),\"populd HDs whose centers fall outside vtd-based county lines.  Assign to closest county\")\n",
    "        for t in unassignedList:\n",
    "            minDist = maxD\n",
    "            for c in range(nCounties):\n",
    "                dist = countyGeom[c].distance(hdCP[t])\n",
    "                if dist < minDist:\n",
    "                    minDist = dist\n",
    "                    HDcountyNo[t] = c\n",
    "if len(unassignedList) > 0:\n",
    "    if len(unassignedList) > 20:\n",
    "        print(\"  (too many to plot individually)\")\n",
    "    else:\n",
    "        print(\"FYI, here are those manually assigned HDcenters to their counties\")\n",
    "        for t in unassignedList:\n",
    "            print(t,HDweight[t],\" is the HD row and its weight in the ensemble\")\n",
    "            plotPoly(hdCP[t].buffer(0.1))\n",
    "            plotCenter(int(HDvPop[t]),hdCP[t],6)\n",
    "            plotPoly(countyGeom[HDcountyNo[t]])\n",
    "            plotPoly(MAP,0.2)\n",
    "            plt.show()\n",
    "print(\"Ready to capture unit centroids based on these HD poly shapes; see next block\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "3f0f8434-5f7a-41d1-bd86-07ec230b4aef",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now, let me renormalize the HDweights if there were cut districts\n",
      "our HDweight sum was 0.999999999999891 but is now 0.9999999999999999\n"
     ]
    }
   ],
   "source": [
    "print(\"now, let me renormalize the HDweights if there were cut districts\")\n",
    "sumWt = np.sum(HDweight)\n",
    "HDweight = [HDweight[t]/sumWt for t in range(nHDs) ]\n",
    "\n",
    "print(\"our HDweight sum was\",sumWt,\"but is now\",np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "id": "c47fa1ff-2bed-4641-96e9-8dbdb7cb6da9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use fraction for corner clusters is 1.00, but can enter higher number to account for later discontig rejects\n",
      "for MN, I suggest 1.3, 1.05, 1.3, 1.05\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxCCBfrac (e.g. 1.0) prior to discontig shedding 1.3\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on cluster no 0 containing counties [27, 84, 22, 78, 54, 49]\n",
      "halfway there! last use was 0.89211\n",
      "our final fractional capture area to normalize this cluster's usage is 0.25889 from 664 intersecting HDs\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxCCBfrac (e.g. 1.0) prior to discontig shedding 1.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on cluster no 1 containing counties [34, 67, 44, 38, 3, 56, 62, 59, 14, 53, 43]\n",
      "halfway there! last use was 0.90822\n",
      "our final fractional capture area to normalize this cluster's usage is 0.07038 from 1406 intersecting HDs\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxCCBfrac (e.g. 1.0) prior to discontig shedding 1.3\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on cluster no 2 containing counties [15, 37, 68]\n",
      "halfway there! last use was 0.82644\n",
      "our final fractional capture area to normalize this cluster's usage is 0.02553 from 1190 intersecting HDs\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter maxCCBfrac (e.g. 1.0) prior to discontig shedding 1.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on cluster no 3 containing counties [66, 58, 52, 40, 50, 31]\n",
      "halfway there! last use was 0.96393\n",
      "our final fractional capture area to normalize this cluster's usage is 0.01079 from 1151 intersecting HDs\n"
     ]
    },
    {
     "data": {
      "image/png": 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skR85oZ0sBXlYCvJQ/EFcn36F0ujHfN5AjP2yOzUOJRQmXO8mXNdAuL4RSadBYzOjcViQbRZRaE1osR77l1AUFWsdv6Ji6tEFxtre5ZTSy4bdYWH3+qMMn5LbgTEJPY1s0JFw+SQAGpZvwbNmN9bzh2LI7biSAWG3F/faHSgu76lve1lCthjRWE1oHGbUQIjg0Sp8e0pQGgOgqnC6cbWyhL53KqZh/USCIgA9MPkIh8OxDkHogSYMHMu6vZtE8iF0GNu0kSiKQsOiDXjW7MRxyXg0ttbP4As3+mhYugXVFwBAMmixjBnYoSv6KsEQvt2HqX9/DSiR7ESX5cQ8dpBIRnqoHpd8bNmxm+H9+sQ6DKHLOfM0yZbIzEhm9a51qKqKJImBu0LHkGUZxwXnofiD1L33BZoEa1PZ9zNRgiHcK7cSrvVEWip0GmxTh6NNtEcvTp32lJWDfXuLqX9nNaqioktPxDJlmGiR7kF6XPJRVlPH6OFDYh2G0MW0N1/oOzyVxvcDVB1xk9JLDBYUOpZs0JF0zTR8e4upeX05kiQhOyzYzh+GbDSgNPpwLd2C0uhDkmUsE/JjXlPEODAH48AcAHwHSql7YyUA5oJ+GAf0imVoQifoccmHuOsU2kpV2976oTNoyOvbmy/X7eCSXmKwsxAdJ1/Qg+XV1H+yHjUYQtJqsE0fEdXWjfYw9s3E2DcTiIxladywD+PQ3GYtJUL30uOSD0Fom/YnrbMnTeDx/z1Pv/XZ5I/t3FkKQs+jS3eSeOXkWIfRarZpIwFwr91Bzf+WostIRDLoCbu9qF4/akiJ7HjyvYB0/PuT/tWlJ2Lom4EmNVF058ShdiUfjz76KAsWLOD222/nySefBGD//v388pe/ZPXq1fj9fubOnctf//pX0tLSOiJeIQZEgbGOkTUwiR9f+m2ef/cNfj/iVrR6MdBOEM7EOmEITBiC/3A5akjB0C8Tjd2MbDSc87lKKEyg+BjeHYcIf3G8auxJLZfaVAeWcYPFejsx1ObkY/369Tz77LMMHz68aZvH42HOnDmMGDGCpUuXAvCb3/yGSy+9lHXr1sU8+wz4A+hEVdNWKw8EyRAFxjrEgFHpmD8zcLiwmn4FqbEORxDiXlumEctaTbOunG/yHyqj/uMvIRxpRZHtJqwTh6KxmtoVq9BybUo+3G43N9xwA8899xwPP/xw0/YvvviCQ4cOsXnzZuz2SN/iSy+9RGJiIkuXLmXWrFkdE3Ub1dTVkWQThbJaq9QXZKRdLMLXESRJYnzeaJZvXku/gstjHY4g9EiG3hkYemc0fR+srKNh6SaUxiDIYBiQiWlE/5jfMHdnbUo+br31Vi6++GJmzZrVLPnw+/1IkoTB8HWzmNFoRJZlVq9efdrkw+/34/f7m753uVxtCalFquvqcTric8DVufg8QQK+0Gkfa+kg2jPvduoDJ+9b1+BHlXR4WtHz0u6YTrNdOv3GVsTU8gC+uTUcVFp+onMYfV4ey5/9klAgLLpeBCEO6FISSLhsUtP3jduKqHtjJZJGhm92OR/vvdEkmNFnOtH1ShMtJm3Q6uTj1VdfZdOmTaxfv/6Ux8aPH4/FYuHuu+/mkUceQVVV7rnnHsLhMGVlZac93sKFC3nwwQdbH3kb1Ls9pCc7O+VcHanuWCP3/P0PJHhTT70qtq/8RIuUJmlZWXP6xKenCGoC6Awdkyg4s6wYLVoOFVbRv0CMhRKEeGMe3v+sC/kpikK4opZAaRW+5VtRA8HmOxz/uyyb9ZiG9435tOZ41Krko6SkhNtvv51FixZhNBpPeTwlJYU33niDH//4xzz11FPIssz1119PQUHBGZuvFixYwJ133tn0vcvlolev6Mzx1kgawkrH3cF2lopiF/qQiYce+BF6U9vHCJ9xquhpNp+8aVmNi+lJ9hMHaekhzpwYnTGMcwTSgkOf9hCtmSJ7hl0lWeqw5EOSJCbkjWHZ5nX0F10vUaUqKpIYLC10MFmWkdOd6NKdUHDm/UK1Lrxb9+NZtxs1HEaSJHTZyaKyK61MPjZu3EhFRQUFBV//tMPhMCtXruTpp5/G7/czZ84c9u/fT1VVFVqtloSEBNLT0+nbt+9pj2kwGJp100STQa/D5w90yrk6UmqOHRmZYwdd9Bqc1ObjnLEr5By9GZIkITf9ARd/yDtCwdiBLPvHWoKBMDrR9RIdGilSylskH0KMaBPt2KaNarbNt+dwU2VX2WrEPmt0j5x106rkY+bMmWzfvr3ZtptvvplBgwZx9913ozlpJklycmRdgKVLl1JRUcFll13WAeG2j0GvxR/oesmHI9VEmi+XZ177L48+eFuswxE6gDPLislq4ND2SgaM7rhFwYSvSVoZNawgacWgQSF+GPNyMeZF1ngKVtZR//4a1LCKPjclMr24h2jVp9JmszF06NBmXxaLBafTydChQwF44YUXWLduHfv37+c///kPV199NXfccQd5eXlReQGtYdTru2TyIUkS37/9IoLBIH9+9LVYhyN0AEmSmDBoNMs3r4t1KN2WpJFQQ50wKEoQ2kiXkkDi1VNJum4aGoeZmv8tpf7zDShdcHhAa3X4LcGePXu44ooryM/P56GHHuLXv/41jz/+eEefpk0SHHZqXZ5Yh9EmKb1sTBhwHluUdRSuOdxp5/WFFfSi2Toq0hKT2X+0ONZhdFuSVoawSD6ErsE0uA9J18/AOKgXda+voO7Ddd06CWl3efXly5c3+/7RRx/l0Ucfbe9hoyIxMQGX1xvrMNrssuvHs+yRZXz4/lqGTuycpdkjBcZ6Xn9kZ9h5cB8ZxqxYh9F9aSTUcPf94y10T4acNAw5aQTLqqj971KMg7KwjM2PdVgdTnSGdiF6oxZT0EbQH27XImetUeoT1U2jIeALsXXnXpwpYoXbaJE0Mqpo+RC6KF1GMs4bI7Wxql9eTLC8OsYRdSyxsFwXEgqEUSWFjdmfcfeCGlKyv75w9UnqzfxvTevwc5o1Mmvq3EhAL6OeAWaDWBm4A2h0MhqHwvgRI2MdSrclaSTUYDjWYQhCu1jG5mManUf9e2vQJlpOmT3TVYnkowvR6jX88aGf89UHB7GNNaLVySBBfaWXjzcvZj7TOvycJ5dVP+z1s7SmAYjMYhxuM5OkE2+httBoZHLTM9m6ZR/ZgxIxWkTXVocTA06FbkKWZRKvnEzjtiKq/7OYxPlTWrTAXjzrcVcOo06Hx9OIxdI11yrRaGUmXNmv2bZjB12wKfrnzjUZyDVF3vAhRWVrQyObQ42ogEOrYaTNjE4MTm2xK+bM5N9vvc/v/rSZH15zHbmDkmMdUrdyYqqtIHQX5uH9MfTPpvb1lVgmDcHY7/QL53UFPS75GD0kj/XbdzJt/JhYh9Ju4aBCOKwQDimoUufe4WllidGOrxfpqwuGWFPnJnh8LEp/s4Hepq6dmUdbSi87d95+A19+to8nX36RJFsCV8+6iIEFGScVdRPaStJIYraL0O1ozEacN82m9p3VhOvdWAoGxjqkNulxyUeCw47L64t1GO2mqip3PvgYAMaQlUR7bAcuJui0TE2KxKCqKge8fhZXRxYJ1EsSI+1m7D28nPDpSJLE+LkDGTn5dnZvPsp/Pn6P8FsKepuGucNnkprlwGTVY7JFumX2e4rwGRuw6W0kGZLQa/Qcch3CrDUz2DkYjSx+xk00ouVD6L4Sr5xM/aINNCzfgm3ayFiH02o9LvnoLiRJoo+9L/vce/jWpRcxZGxOrENqIkkS/cxG+pkj6/8EFIUtrkZcYQUJSNRpGGEzoxEDV5sYrTpGTunNsIk/wlPr5+DuYyzethL/nhABb4iAN0woHGRQ5kBuvu0CXAEX9f566gP1jEwdiSfoYfmR5fR19KWPo0+sX05ckGQJRO4hdGOO2WNwf7mT+s++wnHBebEOp1V6ZPLRPzOdPfv2kzeg37l3jmPXXDmLe1/7Cp2kj+ul2fWyzHkJ1qbvqwIhVtY0NF0X8ixGso1iOi9EBqLak02MmNybEZN7N21XVZWNnxymutSNJEk4DA4cBkfT4waNgZk5M1lWvEwkH4LQg1jHDca9dgeupZuwzzjLKndxpkcmH4MG9OXDFWu6dPLR6Arw0tOLSDX1Iu+8jFiH0yrJei3TnZFVclVVZbfHx5JqFypglCVG2cxYRBdNM5IkodXLqOe4k081p7LqyCpkKVLC58RKwaqqIkkSEtIpqwdrJA1Ok5MkY2TRwgRDAlo5+n8aQkqIkoYSSt2lqKhISITVMCNSRjRLrILBIOXl5ciyjEajafoKBAI0NDTQv39/Mf1b6NGsE4bQsGIr7jWFWCcOjXU4LdIjkw9ZllE6qUhXNHjq/Ty08P/4Mu99fpP1RzRdeOEsSZLIt5rIt5oA8IYVNrsaaTxeVjhNr2WI1YQsLi6RC+w53rdDklu/MFVICVHtreZY4zE0koZ9tfsIq2HcATcTMic0SwTaI6yE0cgadlXvoqShBJveRrYtm/EZ45vGqqiqyoZjG/CGvE0JVFFREevWrcNoNKIoCkpYQVEUZI2MR/Xw0+k/Zfjw4eh0Yrqy0HPZpo6g/vMNNG7Zh3nkgFiHc049MvkAsJuMuN0erFbLuXeOM5sXH2Zn2hd8v/o3zPh/w2MdTocyaWQmJn7dRVPuD7L8eBeNDAyxmkjrqeXeJVCUjk+atbKWNEsaaZa0ZttVVWVpyVJm5sxs87FL3aXsr9tPSAlFWm9kLSmmFOb0nnPa/SVJYmz62ObxlWgx5hq57rrrTtn//97+P/731f94ceWLOBOcTB0wleH5w3E6nW2OWRC6KsecMdT8byn63uloE+K7enKPTT6ALtlUW1/ZyDsbPyLFlMP8O8dFBtV1Y+kGHenHkw1FVdnh9rLd7UUCTLLMKLsZk6brtvy0hixL52r46FCSJOE0Oqnx1TR1ybTWscZjDEseRoIxoc1xhMNhNJrTd8N9f973URSFsrIyDh85zLI9y3h9zevY7DbG9xnPSFs+vfs7kOWe8R4RhISrp1Lz8mKSvjM7rt/3PTb5UFW65IW70RXgYNJWTEEbVSUNZA9q20WhK5IliWE2M8OOf+8Jhdno8uBXIqMYsgw6BlmMXTKpbAlFUenslxZUghg1xlY/LxAOcNh1mDJ3GdnW7HbFcLbkAyLdqFlZWWRlZTFx3ER8Ph979+1lxa4VLC1cgnaDjqE5Q7Eb7FR4KqhprEGSJOYOn8vYEWPPeFxB6IpkrQb7BQXUv/MFiVdNiXU4Z9SDkw+1S16k0vo4mLb/W6zo+xrLv9jItwfNjnVIMWPRapic+HXTYokvwNKaBlQiXTTDbWaS9d3nLa4qKrKmc9+zlY2V7JZ208fRp2mwqqIqGDQGfGEfRXVFuANudLIOWZKbPlM6WUeuPZcL+1zY7s/ZuZKPbzIajQwfNpzhw4bj2V3FMb2LdbvW4Q646ZPYh/Nyz6PeVc9LS16iYGhBq44tCF2BPjMFX2IJvl2HMOb3jnU4p9V9/jK3ksVowOP2YDK2/q4ulmRZ4pIfjWL9xx8TrovfJrVY6GXU0+v4lN2wqrKtwcuWhkYAbJpIF40+jpshz0UJq53eWndR34twB9wcch0CaJox4w/7MWlN5CXmkWhMjGoMrU0+TqaRNfTt25e+fftSW1vLK0teobC8kIOlB/FKXhRFEcmH0C3ZZxRQ/e/F6PNy4rL7pccmHxnJSZRXVZOc3PUGpn20dCW7UteSvTcPaPtgwO5MI0mMOmlRPFcozLo6D4Hjgyb6mPT0NYkVelvCqrcyNDl20/fC4TBabfv/VL266FU8bg9jB4xl7tC5pKSkiBkyQrdmnTaMhk/X47hoXKxDOUWPTT7S0lIo2riNrjEjurkr5k6n+OWjyIg7tpayazWcn/R1F83BRj9Ljq/Qq5MkRthMJMT5Cr2yRkKNwmyXeBcKhdDr21+ErqisiFRzKv1y+uFwOPD5fBw4cACv10tjYyNl9WVUe6oZ3ns4BcMLRGIqdHmGnDQav9xNuKERjS2+FlON77+2UWQyGvGHQrEOo00kGQrTV5FbOxhV6fym+O6gj9lAH3Nk4bugorKloRHX8RV6k7QahtvMaOPs5ypJ0jmLjHVH7el2OdmDtzzIyx+/zBPvPYHP60Ov16PX6zEYDBj0BpItySSaEnlx+YsUHijkmrnXYDKZOuAVCELsOC4dT917a0m6dlqsQ2mmxyYfXdmOL4+goqBRdCiqiob4ukh2NTpZYuxJK/TWBEOsrmsgdLyRYYDZQG4crNAryVJU6nzEu45KPqxWKz++5seoqoqqqmfsB7+o/iIW/nsh9/7jXp6444l2n1cQYkk2GiI1ghp9yOb4GeMoko8uaN2hr3AYU5g//Ao0PaTGRWdK0mmZlvR1+fd9jV+v0Gs4PpbEGoPy77IMoUC4088bax2VfJwgSdJZu1QcDgeZzsxTytC3VCgU6pAxKoLQURwXjaP+k/VxNfW2R39CpC7aYnD+sHHs3rsJk65nNQmvXLmSxx57jI0bN1JWVsY777zDFVdcEdVzSpLEQIuRgZbIHYMvrLCloRH38aXaU/RahnVS+XdVhYpDrqifJ950dPJxLoqisLNsJwvmLzjrPvv27WP93vX0Te2LVtJSXV/NusPrKK4rJseWQ0ZKBoFggGPuY1w++nLOG9m1Vh0Vug+N1YQaDEeWJYiTmS/xEUWMtPXOJtbOv3QIveryeXfNZwR8XXPcSlt4PB5GjBjBM888E7MYjBqZ8QlWZjntzHLaydDrWF7TwOJqF0uqXZT6AlE7tzPLisHc82ZndHbyIcsy0/On89ynz+H3+0+7z0eLPuKJz57AH/azdO9S/rn8nyzdu5RROaO444I7mDBwAmm2NLISspiWO41nljzDps2bqK6u7rTXIQgnM583EM/KbbEOo0mPbvnoqjQ6GUUKsy1jOUd2XU3fUSmxDqlTXHjhhVx44YWxDqOZVIOOGSeVf9/l8bHzeBeNUZYosFswd1DXmKyVUMI9b8RpLAoCzr9gPof/c5g/vfInfnzFj0lM/LqWicvl4tUdr/KTCT9h0oRJp33+cL5ecykUCoEO/vPFf/Au8/K3O/4mZtIInc7YN5PG9XtjHUaTHt3y0ZVl63IJaL0c3Fse61CE42RJYojV1NQqUmC3sNnl4fXymg5ZRVmjkQmHu2ZrXVej0Wi47ZrbcFqcLHxlIT6fr+kxm82GLWzDYmrZopRarZbZU2eTn5XP6NzRIvEQYkbSaVAafefesROI5KMLUlWVo8ESUty9GD6hd6zDEc7ArJGZlGhjUoKV3Z72f+BljYTSA5OPWF2sTSYTP5j/A1KsKfznw/80iyfHmcNHGz7C5Wr5GJyRvUay8vBK1ny5hiNHjqB25iqBggDYpo/AtXRLrMMAeni3i8Nsorq6Bqezay3OFvSFcRmq6FWXT3K29dxPEGIqy6hnV7WLwdb2DRCWNRJKqOd1u5SXl9OnT5+YnFuWZX54xQ/56f/9lKHrhiJpJb7a9xXH6o9RrVazbtM65kyb06JjjRg+glt8t/DMF8/g0/iYoJmAPcuOzWBj3sx5GAyxn859LoqiUFdXx/5D+3ln4zvotDoC4QDn9T6PK2ddGevwhHPQJtpRvacfx9TZenTyYTOb8Hh9dLUC61VH3OxOXYcl6KCu4gckpres+Vfo2mSN3CNbPmRZxm63x+z8DoeDq4ZexT9X/RObzsbYfmP5yUU/ITk5udlYkHPR6/VMnTyVwXmDef6D59GatSSZk9hZvJO7nrmL+WPmEyBAamIqAwcMpK6uDlmWSUhI6JAKr+1RXl7Ovxf9m8MVh1HDKja7jblD5qKqKhWlFazYuUIkH0Kr9OjkQ6/T4g9Eb3ZCtCRlWBheNg2NokMWdT66jPYOnNRoI0XGuuqKzG2l1+tjvgbL5XMu5/yx55OYmNjun31KSgr3fO+epu9VVeXl919m8f7FGDVGyjeX4/3EG1lBWFKQVZm7593NgP4D2vsyWkxRFA4cOMCmok3srdjLgWMHmNZvGt+98bskJSU1q2NSWVnJ8n8tp7KykpSUnjH4vSuTzAZCtS60ibFL6KHHJx96fIH4aIJqDZ8niMtYzZzgVdid8VOxLtrcbjdFRUVN3x88eJAtW7aQlJRETk5ODCM7t/5mA0WNfgZY2v77OpFoKmEVjbbnJB+SJMV8fIQkSSQlRad7VpIkbrr8pqbvVVWlsrKShIQESktLueede1i5cWXUkw9VVSkvL+fjdR+z7fA2QmqI4TnDmdx3Mj+68EdnTCxsNhuN2kbufvFuLs2/lEnnTSI1NTWqsQptZ504GM/aXTFfbK5HJx8GvQ6XxxPrMFrNmmTAGLSwis+4yjsWo6Vn1H7YsGED06dPb/r+zjvvBOA73/kOL774Yoyiaplco54lNQ3tTD4iCUc4pKDR9pwWr3hIPjqTJElNF++srCwmmSaxuWxzVFu8gsEgL7/+MosqFjE1eyp3Xnkn2dnZLaqvYjQa+ev3/8q+A/v4w4o/UO2r5vvzvx+VOIX20ybaUbyxb/Hv0clHgt1GUcnRWIfRapIskR8oYItlNVpdz7kITZs2rctehDrionEi+ehp4z56WvJxMp1Ox6D8QWz+ajNvfvYmBQMK6NOnT1OVSq/Xi8FgaHPVynA4zOufvc7afWuxm+w8csUjbRrc63A4SLQn4tV6KTlUctp9GhsbKS4upvBQIfsq9jGm3xhmT5rd9Hhrqm8GjneX+3w+AoEAkiRhNpvFQoBdSI9OPqw2Kx5/7DPA1tJoZG576DIW3FfCQ/f+mwcf+26PGgPQVZ1Y0Kytv6sTrR09LfmQZRlF6XmzfJroQK/o+WT7J7y/433Sjeno9Drcbje1Si1z+s3hxitubNUhVVVl09ZNvLr2VYyykR/P+TF5eXntKr3dr18/Xrj2Be5+8W5ef+91PHio9dVS7aqmsbERr9+Lw+6gd0pvSkpLKDpWxMbDG2n0N9Loa8TtcmOxWdDKWvwBP6N6jcJitrCrfBc19TUYjAaUkII/4G9WeVaj0aCqKoqiYDKZcDgc5CXnMWHIBHr16tWp1XG7jDhI5tuVfDz66KMsWLCA22+/nSeffBKIjIq+6667WLRoEQ0NDeTl5fHrX/+aq666qiPiFY7TaGVuvuwqHl/8VxqqfdiTRcYf73JNBop9gTavkPt1y0fPuhCHw2EqKioYMmRIrEOJidkTZzN74mzC4TB1dXXs2L2D5MRkPB4Pzy17jovPv5hgMMjRo0eprq5GkiSysrJIS0sjGAyyvXA7JVUlBMNBPAEPJXUlVFRXIGkkbph0AyOHjeyw2TQpKSnccfEdfL7tc7LsWWQlZJE5JBOHw4HD4WiatXTkyBE27NpAkjkJh9WBLMtkZWVRVlaGVqtFo9GwaOsifB4f43qPY1CfQdTX12MymTAajU0Dfw0GQ1Ny0djYSFVVFRWVFWw8tJE/vfcnBqUM4gfzfxDz2UJxJw5uVtucfKxfv55nn32W4cOHN9t+0003UVdXx/vvv09ycjKvvPIK11xzDRs2bGDUqFHtDlj42oAxaUzYOonH//ESP7/lRpIyxJTbeDbAbGBJTUObkw9JkpDlnldozGQycfRo1+se7WgajQan08n5k84HoLCwEIDnP3meg2UH0ev1JCYkUlVdhV/yk5mQSXVdNVqdlj4pfdBqtCQYE5g2YBp9ZvYhLS0tKqvvDhs8jGGDh511n+zsbLKzs0/ZfvKg3v79+7fqvGazmZycHHJychgzegw1NTUsfHUhz7/7PD++5setOla3F/vco23Jh9vt5oYbbuC5557j4YcfbvbYmjVr+Pvf/85550VWcLzvvvt44okn2Lhxo0g+OphWr+GWH13M0397gw2r9zLnavHzjWcd0TWmKCrBQLgDouk68vPz2bdvX6zDiDsZGRn0z+rPsMxh3DTrJlJTU5EkCUVRWLluJUadkeyMbDIzM+NmJdPOlJSUxJTsKby9922m755OUlISiYmJp0zbrqurw+VyUX6snAZvAw6zg9zc3Gaze3w+H6qqijElHahNycett97KxRdfzKxZs05JPiZOnMhrr73GxRdfTEJCAq+//jo+n49p06ad9lh+f/P+u9aUKxYig09Ttems3vUVs5WRSHIcpLRCVPkbe85KxhAZ89FTB5yejdPp5Fc3/OqU7bIsM23itM4PKA7NmjWLmkANf37/z6ioaBUtD9z8AKmpqRQXF/P8B89T7ivHZrBhMpuwmWwUlhUiqzJ2jR1ZK+Pyu9AqWkJyiPnD56NRNawvXE9ZsAyj2cgff/LHqLQgdXet/om9+uqrbNq0ifXr15/28ddff51rr70Wp9OJVqvFbDbzzjvvnLEJbeHChTz44IOtDUM4ySXXj+OrP26g9lij6HqJcxkGHaW+AJnGtvVBWxx65B6WYMqyTHFxcZuf39OKsglfM5vNfHf+d7kxfCMul4tH/vUIv33xt2hkDYqioFW0/PqGX5Obk9v0HEVRKCkpQaPRcOTIEV5e/jIunYugHOQvRX/BErJEurDCCZzf6/yuOaA1DnL5ViUfJSUl3H777SxatAij8fT1Cn7zm99QV1fH4sWLSU5O5t133+Waa65h1apVDBt2aj/gggULmuo1QKTlo1evXq18GW2XaDVTWVlFSkpyp52zo8myRFgKEe6B6350NfkWI8tqGtqcfPREaWlpBAIBQqFQ6+8wZUABuuD1Qeg4Go2GxMREHvvFYwSDQWpra89Ytl6WZTIyMnjg2Qeobqym2lTNY5c9RkVFBQaDgYEDB2I2m2PwKrqXVn2SN27cSEVFBQUFBU3bwuEwK1eu5Omnn2bPnj08/fTTFBYWNo1MHzFiBKtWreKZZ57hH//4xynHNBgMMV1QafSQfFZs2MycLpx8mGx6+iX34U9Pv8wvb7tJLDYXx2RJatdNhwpxMVisMyUnRz6bwWCw1cmHpJFRwwpSV7w7FaJCp9OdsQKrqqrs2bOHv3/4d+qpZ8EVC9ixfwcpKSkxW9ywu2rVJ3nmzJls37692babb76ZQYMGcffdd9PY2AhwyuAmjUYTt/P0DUYDwW4wdfEnt13FH+98i3uff5R/3v/wuZ8gCD2BRoIeNjtIaL1wOMyuXbt4ZekrHA0c5ZpR1zB9wnTMZjN5eXmxDq9balXyYbPZGDp0aLNtFosFp9PJ0KFDCQaD9O/fnx/96Ec8/vjjOJ1O3n33XRYtWsSHH37YoYF3pO4wmE2jkcl2ZlDEJtHHHeecOi2VgSAp+jaUxe/6b9VWO/H5bMt7+kTLhyCcLBgMUl9fz979e9lcspmt+7eiSiozhszgnin3xHQV5Z6iQ4fo6nQ6Pv74Y+655x4uvfRS3G43/fv356WXXuKiiy7qyFN1KIe564/7ABg2OYela0L8/fH3+MldV8Q6HOEMhllNrKptYLqz9cmHqqo9bsBpu5IPrYQaJy0fCxcu5O2332b37t2YTCYmTpzIH/7wB3Fn3Uk8Hg/vLX2PXRW7qK6rRgkrpCWnMarXKC646gL69u3bc6Ykx8ENd7uTj+XLlzf7fsCAAbz11lvtPWynmjh6OB+tXMtl0yfHOpR2GTkjh18Z7+CZT1+gtnw2ieli5ks80soSba3UoaodUy+kK2lP8oFGhjgZiL1ixQpuvfVWxo4dSygU4t5772XOnDns3LkTi0V8VqMhHA5TWlrKG8veYMexHYSlMP9v6v8jNzuX9PT0HvdZAlCCIYiDGxgxOZnjawPEOogOkjcuHfu7yTzw9NP85eG7Yx2O0MFUVUXqITdn39S2bhcJNRgfycenn37a7PsXX3yR1NRUNm7cyPnnnx+jqLqXUCjEjl07WLN3DYerDuNyu1BCClpVyy8v/yV9+vQ540zNnsK7/QDGgVmxDkMkHyf0y0ilcPUaBheMRO7C06hkjYyERIW1mM/f3MSc+QXnfpLQ6RK0GmqDIRJ1rfwI9uCWj7aQNDKKLz4rwtbX1wPNS4oLrbN3314WbV3EsYZjNHoa8TR6cGldjLaMZt6oeaSmppKTk9NzulNaIHDoGI7LJsY6DJF8nDB00EA+OWim744dKF5vZKMkgaqiTUvH0Kc3UhdZnOh3j/6AP9zxJv+S/g/L5z9l0pzBsQ5J+IZhNhNf1nk4P8nWqucpitrjptq2r9tFgjgccKooCj//+c+ZNGnSKYP4hVN5vV4OHz5M4aFCth7dSqO3kUAggCIpzBo8i0n9J+FwOEhISCAUCuF0OkXCcSZhBVkb+6nnIvk4idXhINwrA9tJvxhVVQlVVNC4aRNqIPD1zpKMLjsLfU5O3NUQkGWJe56Yz19+auUpnmL8zL+h0YgPYjwxyDKBNtzRS5LU42a8dJcBpye79dZbKSwsZPXq1bEOJe54vV4qKio4VnGMnaU7+eTgJyT4E7Db7fRL7ceVBVfiTHJGFtJLTOzx3ShdlUg+TjIp0cqiahcXJDuatkmShC4tDV1aWrN9VUUhePQonrXrQDmpWVejwdC7N9rMzJg2j0uyxC0PT2ffkxvZtvIwo6aLAjndQU9c1faENWvWMGXKlFY9R9LIqHEy4PSEn/70p3z44YesXLnytCu79iSqqlJfX8/BQwcpLClkS/EWPG4PJpOJBEcCfZL6MF43nuuvu5709PRYh9vlNW7Zh75/RqzDAETy0YwsSZhlGXcojPUczVKSLKPv1Qv9N0rBq8EggeJiPKu/ANSmKU2S3oChX180ycmdlpQYrToUKcwrn7/PsEk/RauPrxaans6iadl77WSypuclHxaLhaFDh7JkyZJWJx/I8VNkTFVVbrvtNt555x2WL1/eoytm+nw+Vny5go82f0QgEMCZ5GRg6kBumHgD+YPyxeqxUeLbc5Ska6fFOgxAJB+nmJRo5fMqF3NTHOfe+TQknQ5Dv34Y+vVrtl3x+QgcOIBv9+6vN6oqssWCoX9/NI62ne9sdHoN9157G4+89lf+tvBDbvvNZWLV2zgywmZmk8vD5MSWj/uIJB/xdScfbbIsM3HiRPbv39/q58bT+/3WW2/llVde4b333sNms1FeXg6Aw+HoERdbj8dD4c5CPtvxGaUVpSTaE7nt4tvo3bv3KcvcCx1PUZS4qO9xgkg+vkGWJFINWoq9fnJMHbfmjGw0Yhx86sDPsNtNoKiIcENDs+0ahwNDv37I7Zz/32twEnfN+zFPvPl/+BsvwmgVH/J4YdbI+JTW/THoiS0fEKnX0NWXLf/73/8OwLRp05ptf+GFF/jud7/b+QF1Aq/Xy/79+1m6Yym7infhTHQyK38Wo64chSMKN1zCmXlWbcc8dkCsw2jStT/NUVJgt/BBRV2HJh9norFaMY0cecr2UG0tvp07IzNvTnTTqCratDT0ffogt2LmTWa/REKaAKve28PsG8TI+q5MkiSUOLp76SyhUKhrLl1+ku6wjENLqKrK7j27eX/D+xwqO4Tdbmd0zmhu+N4NOJ3OWIfXYwXLarFNHRHrMJqI5OMMRtnN7HB7GWKNTXOoNjER7dixzbZFZt5U4j155o0kARK6rCz0Ob2QTnN3aLTqSPJk8tr+/5Gy9IeMnJHbCa9AaAmjLNEYVjC3dDaSRI+b7QLdo+Wju1MUhe07tvPamtdw+9xcOOxCvn/h90XCEQf8h8rQJrduWn+0iU/zGWQb9eyoqo9Z8nE6kZk3qejSmi8HrSoKwdJSPF9+CeHwiZ1BltHn9kaXmcHDf/gBCxb8jbc/XsLIGd+LQfTC6Yy0mdna0MiEBGuL9u+JU22he7R8dFfhcJjNWzfz2pevEQqHmDdmHuNHjxfjOOKIZ+0uEuJkoOkJIvk4i3atPtqJJFlGn52N/hvT9tRQKDLz5os11NYqrO39HpMOzsOzbh36vn3RpqT0uGqZ8caq1eBp5QBStQdmH6LlI/4EAgEWrV7E54Wfo9fqmX/efEaPHC1+T3HGf6gMbYoj7oquiXfJWYy2m/n8G3U/uhJJq8XQty+Gvn3ReUM4n8mkUe/CNGoUgYMH8e/Z8/XOqopsNkdm3iQkxCxm4eykHtrtIlo+4svmLZt5YfkLJFmTuHXurfTv3z/uLm5ChHvVDhJvmBHrME4hko+zkI7X/fCEwljioBxte7gqvSR602nUNaBqdRgHDYJBg5rto3g8+PfvJ7x9e7PtGrsdfb/+aKxi5c1o0EsSfkXB0MI/3j0w9xAtH3HiwIEDvLzsZQ7XHGbuoLlcfcnVovU0jrlXbcM0ondcJobi03wOExOtLKl2MaeLtn6ckJhuxhAyYwxakM9Q+0C2WDANH37K9nBdHf49u1EaG7/eqKpoU1LQ9+2LbIj+rKCuLBQI4KmroaGmGk9tDe6aakr37GLvl1+QOTCf8275CVtlifNaMu5DjPkQYqC8vJyFLy+kUW1k3th53HH1Hdjt9liHJZyF4vMTKKkiaUr8tXqASD7OSSNJaCSJgKKgj8PssaXcdX7K7PuZcezaVt+paBISMI8e3WybqqqEKivxbt6CGjxpzRskdFmZkTVvuvmdqqKE8bpcuGuqcddWH/+35pR/fQ2uMx6jdO8u3r37NkoHj6YmJZHcEaPIHTYSs/30yW5krcOel32Ilo/YqKys5PVlr7O9ZDsDUwdyyxW3iPocXUTdu2tIuCL2q9eeifg0t8DkRCsrahqY3YVbPxJSzVj8CehDHTN7R5IkdKmp6FJPN/OmLDLzRjlpIKUso8/NRZeZiRTnSZyqqvgbPcdbKWpOSiyqv/6+tgZPbQ2qcubBopIsY0lIJL3fAKxJTiyJTmxJTiyJSVgTkwj4vNQcPULZvt0cqm9kx4rF7FixGCSJtD79yB0+it7DR5GZl49GG9+DnqNNtHx0rlAoxK8e+xUNmgYm5U3i0VseJUGMBesy3GsK0eemIpvjd9E9kXy0gEGWMcgyDaFwsxVvu5LyA/XsTl1HwdHZqKoatX7ayMybLPTZWc22R2belOD5Yg0n9xtIOh36Pn3RpnbOzJvTdYF83UrxdetFyO8/63F0BgtmRzpGSwJ6swOjJQGDxYHBnIDBEvnSG22nTbTCYaivjvzflJBD37ETqVa89M4vpv7ILqqP7OTYgSKOHSjiq3ffQKM1kJg1EGd2PlUlZpRwz1sTRLR8dA5VVTlw4AD/Xvpv/JKfB254gKysrHM/UYgb/uJjBI/VkXjl5FiHclbi09xCk9u55kusJaSamb/tLj4f+AI3H5tOYnrnDh6NzLzpg6Fv8wunEghEZt7s3dNsu2w0ou/fH21iYouO3xFdIABavQFrUhLWRCfWJCfhsIniHX5Se6ejNTjQ6m1odTZkzaktESoQDEGwHtz1KuBq/uBpnOhCsWpU9uhS6JOQSnbCVEIBN57aIjw1RXhq91F1eDtVhyMDgRc9+xF9RhXQe/gocoaOxGhtWY2QrkxRFDGwMcoaGhr403/+RKWvkllDZnHJdy8RtTq6GMUfpGHJFpJvviDWoZyTSD5aSJYkrNqu2/pxYk2Xowl7Obq3rtOTjzOR9XqMeXmQl9dsu+Lx4D9wAO/27QQCARo9DXg8bryhID6DnkZPQ8d1gSQ5sR7/12C2NLvIleyuwVW7h2vumxC1n8EJi6tdzHKePIgv0l+rqipVJYc5vHUTh7Zt5uiuHWxf8hnbl3yGJMmk9xtA7ohIMpIxIA+5G3ZPmEwmKioqYh1Gt7W3aC9PvPcEA9IGcNdNd2Fp55pSQudTFIWaV5aSePX5sQ6lRUTy0QoTE6x8UlXPxSkJsQ6lTfSygb5VIzENi4+7mXN1gXhqI4+dqwvEYDCSmJyKLS0dqzP5eFLhbJZUmB0OZLn1F2WNViYciu0qspIkkZLTm5Sc3oy5dB7BgJ+ju3dyaOsmDm/bTFnRHsqK9rDurf+hN5nJGTqc3iMKyB1eQEJaekxj7ygajSayKqfQ4Xbv3s3CDxdy/cjrmTtrbqzDEdqo9r9LccwdjSaOqnKfjUg+WkGWJHKNeg57/eR2wqJzHe07d03n8zdf5N3XV/OLgnlRO0+0ukBODNT8OqlIxpKYiFanJ1xVhf/AQdTASYmKN4AuUUZvtSG1IfEA0Opk3DV+SvfVkjmgZV1AbSUBYVVFc47uBZ3eQO/jg1EB3DXVHN6+JZKMbN9C0fp1FK1fhySrJOUkkT20Dyn900jIsKOo9QQCVfgDlQQClWhkI07nNJKTZ2I2x++aP5Ik9chZPtGkKAprv1zLC1+8wAV5F4jEowur+d9SbNOHo8tIjnUoLSaSj1YaajOztNrVJZMPvUmLw5fMgD45bXq+qqoEvI2R5CFas0DO0gVyNtqUFLQpKafEGyotpXHDBtRQ6OQA0OfmoMvKOufMG2e2FbNDT8XhhqgnH4OtRna5vQy1mc+4j6qGCQRrCQSqCPgjCUQgUIkus4rc5ErSJ4PX04g/UAnSibosa6jyQtWB0x+zpvYL9hX9HrO5PynJM0lOnoHDMQpJ6n7dN0JEKBTi9//3e6r8Vdx24W2MGBI/q50KrVPz6jLM4wahz049985xRCQfPYhOryGrPo9x1ww85bFTu0CaJxct7QIxWm04s3o1tVR0ZBdIa0lSZLVf3TdG66vhcGTNmzVrQf06SZK02siaN6mpTUmPRiOT0S+6g4xVVSUUasAequTLmmqSG4+dlFxUEQhU4j/+byBQDZy9+0GSdBiMTvT6fui0SQQ8GtyVXmpKaqkvbSDk1RJs1KKRHOSM6E/yoDCy9QDuxm0cLn6Ww8XPotMlkeycTnLyTJKSJqPVxnYMgGj56DjHjh3jtU9f44jrCH/56V8wm8+c7ArxS/EHqf3fMmyzRna5xANE8tHtndwFsmdtEYvyXmDwUyF65Rla1wWi00cSiNO0UJzcBaLTx3+LkKTRYOjTB0Of0828OYR/715OXrs+XKMSTm/fOJna2i/xeIqOJxJfJxUBfyWBYBWKEinUtp8CbGw6XdTodElYrQPR61PQ653o9SkY9CnHv09Gb4h8r9U6zthi5Kqq4PC2LRzatpni7VvYs3I7e1ZGHkvOnUL2GAuWjBp8ynbKyt+irPwtJElPUuJ4kpNnkZw8A6Mxo10/CyE26uvreemdl9hauRW7xs4ff/BHkXh0UcHqeurfX0fitVPRxHEtj7MRyUcbxMP9V1u7QJwT9ZTULaF+WeRiKkkylsRzdIEkOjFYWt4F0lVFZt4MhLzmLUOawi2E61y4V606viWSmMhWK4YBA9CcY6prQ8MONm3+1mkf02rtGI3ZTQlEsjKEvraZGIzJ6PXJTcmFTpeELLf/42pPTmXYjDkMmzEHRQlTcWA/h47Poinbt5uqw8cir1mXS+7YZJwDg2DZT3XNSqprVrJn72+xWYeQfLx7xmYb2invC9Hy0T6bNm/iH4v+gUbV8PBND5ORIRLIrqpxWxG+HcUkfWd2XK7Z0lIi+WgDgyzhDSuYNNH5xUerC8RoSWBp5evoTDO44b7LO7ULpCuTtFp06UlYpzQfKxN2ufDv3Yvi8TTbrklKwtCvH7IxckdiNvfBoE/DHzhG/36/IiFhXFOyodE0bymye/34FJU+lujfzciyhvT+A0nvP5DxV12Hv7GRkp3bj8+i2cSBNWUcWAOQiCM7lewxJsxpVTS4d9Lg3sHBQ09hMKQ3dc8kJk485fUIsRUOh3n343d5b+97XD3yai6ZfUm3v4norpRQmPp3VqNNSyDp+vhcr6U1RPLRBqNsZrY0NDKhJQuBtVLhskV8/uxfUdUz9+u3tQsk4A2R8ORGdvcqJq1vf/FHqKUkUE/T3qWx2zEXFJyyPVRdjXfbNtSTksMs5RIO8Dx1tRvIzf3RGU+VY9SzpKaBvE5IPr7JYDbTf8w4+o8ZB0DdsXIOb9vMoa2bKC7cyo53GwADWlN/MkcaSBrgJ8Bhjpb+j6Ol/0OWTTiTJh/vnpmGXt9xI+9Fy0frLV62mNfWv4ZBa+Bn037GmNFjYh2S0Ea+vcV41u3FfvF56JzdY0E/kXy0gUWrwRuOTs2BysMHUVWFzLzBpOT2+UZS4WxXF4jepGVY2VRW93mLnatL0RnP0eLRir/1UbsutOLArQqhFTs3VPtIybG1eH+t04nW6Wy2zaxM4Nja5VTVLKV0xT+xy/mRByQZfU4vdNnZSLIcVwlhQlo6CbMvZMTsC1HCYcqK9nJ42yYObd1Eybp9FK/VImn64MjxkzFCizGlgsqqRVRWLQIkHPaRTeNELJYBcfXaujOfz8dT/32KvdV7mTdqHnOmzxGl6buocKOP+vfXoXFacd40K9bhdCjxjowzRlvkIjf64ssZOG5Shx+/1F7EgKrR7FlX3rInROl6EbW1ZVpz2Bbuq9XLpOa2725DlrUMzL+fzVtu4oj5Q8aO+T6SJKOGwwSPHGk288anaHDrJAx9+6BNS4uLi7as0ZCVl09WXj4Tr74Bn9tN8Y6tHN66mUPbNrHr3QogE1NyEsmDQiT281HPZupdm9l/4DFMxhySk2eQnDyThISxyHLrBvCKlo9zCwaD7Cvax58+/BPWoJXHfvwYiS1cnkCIL4qi4PpoHYo3QMJl4+N6gbi2EslHnDHZItM6fQ0NUTn+T38xj1d2vcK8iaOjcnzhzJKSJuF0TqO6ejnl5e+RkXElkkaDPjcXfe7XBb4GNfqoCIbIPFaKf1/R8a2RC69kMGDo3x9tUlIMXsHXjFYrA8dNYuC4SaiqSl15adPA1ZIN2ylZ7UVnTcCe00BKvgLOo5QceZGSIy+i1dpwJk0lOXkmTudUdLqWTWU+ePAgfr8fg0GMKzmZy+Vi3eZ1vLvhXfQ6Pdeedy0zJ88UqwB3QUowhOvT9SgNXmyzRqFL7b7Jo0g+4ozpeMtHY31dVI4/MHEgJm3XKL/bHfXvfw81NavYf+BxUlMvRKM59Y6mn8nAEm+AvgMHwsDmM28Urxf//gP4duwkVFGB4/LLkGLcpC5JEokZWSRmZDFq7qWEQ0HK9u7h0LZNHNq6md1vFyFrE7Fle0jo24gjt5FjFR9yrOJDJElDgmPs8dkzZ66ymns8OausrCQ7O7szX17cOnLkCE+99xQ1nhrSEtK4a95d9O7dOy5ayoTWCVa7aFgcmWJvmzUKnbNrLmDaGu36q/Xoo4+yYMECbr/9dp588kkOHTpEn2/UTjjh9ddf5+qrr27P6eJKtD7e1qTIID1XVXQW0VJVlYP1B6NybOHcVDWMyZRLY+MBSstep1f2Tafsc7aLh2wyYRo6BCAy9TcO7241Wh3Zg4eSPXgok6+7iUZXPcWFWyOzaDZv5vDSKixpXvJmZmJMraC2bh21deuaV1lNmYnDPrKpympSUhImk0nczRPpXvlq41e8vPZlrhh5BQVDCkhN7XpFpno6pdGHa8lmFK8f2WQgYd5kZF3PaQ9o8ytdv349zz77LMOHD2/a1qtXL8rKyprt989//pPHHnuMCy+8sO1R9iA+d6S7xWSPTuarqAqHXIeicmzh9ILBOsqPvU9Z2Zs0NOwAQKOxYDL2avexu8JdrtnuYNDE8xk4fhJLnv872xZ/ihTMYeR5j5CYnklj40GqqpZSWbWE+voNZ6yyqihKl65r0BGOHDnCn9/8MzqTjpun3sy4gnGxDkloBd+BUrxb9qOGwkh6Lbapw9Emdo/ZK63VpuTD7XZzww038Nxzz/Hwww83bddoNKSnN19F85133uGaa67Beo5CTEJEoDFSM8Jobfnsitbwhrwkm7rO4kNdlaqGqalZTWnZm1RWLkZVIxVMExLOIyPjKlJTLjxryfIsg44jvgDZRn1nhRxV4VCIT//2BLu/WEFCegZX3/d77CmRu3WzuQ85ObeQk3MLwWAd1dUrqKxaQnX1imZVVgcMTKW2NhGH4/IeVWVVVVUqKyt57J+PUWWsQqNo+OfP/tnjE7GuwneglMYNe0EBfVYSjovHIxviY2XxWGpT8nHrrbdy8cUXM2vWrGbJxzdt3LiRLVu28Mwzz5xxH7/fj/+keggu19nLfHd3oVAQiDRdR8O2ym3M7S1Wr4yWxsaDlJW9RVn5O/j9kRlFBkM6GRlXkZF+VYtXjs2zGFlW09Atko9gwM+HTzzKgU3rSc7pzfxf/w5LwukH0ul0CaSnX056+uUoSoC6uvVUVi2hqmoJiYlHOFr6GEdLH4tJldVYqKqq4rkPn+PQsUP4jX6uHnk1s8/v2pUtewIlFKZh6SbC1Q3oMp0kzD9f/M6+odXJx6uvvsqmTZtYv379Ofd9/vnnyc/PZ+LEiWfcZ+HChTz44IOtDSPmojXpT6uLXGxCgbNXL22riVkTKW8sxxfyYdR2v+lbsRAKeaio+ITSsjeor98AgCzrSUu9hIyM+SQlTWz1CrGyJMVFGf/2CngbefexhynZsY2M/nlcueABTC1s1ZNlPUlJk0hKmsTAAb/h8cfv4JJLeuH2rMHl2tqqKquqqnapBEVVVb7a9BX/WvEvzh9wPndef6eY5dMF+PYfoXF9EchgnTwEfWbKuZ/UQ7Uq+SgpKeH2229n0aJFGI1nv3B5vV5eeeUVfvOb35x1vwULFnDnnXc2fe9yuejVq/194V2VyRbp//OeY6G39hiVOor7vriPx6c+HrVzdHeqqlJXv4Gy0jeoqPyEcDiyfL3NNozMjPmkpV3a4imk3ZXX3cDbC++nvGgvOUOHc/kv70NvattCZqqq4vEkkJn5fRyOX+D3V1JdvYzKqiXU1Kw+e5VVjQRhFbRdI/moqanh/mfvx6/x84srf0HegLxYhyScgaIoeDfuIXCoAlVV0aUnknCNaOVoiVYlHxs3bqSiooKCk0pKh8NhVq5cydNPP43f728ajf7mm2/S2NjITTedOpr/ZAaDQWT0J3GkpgFQW3Y0aufo4+jDrJxZfHjgQ7ZVbuPecfdG7Vzdjc9XRln525SVvYXXexgAnS6JzMzryMyYj9XacReKVL2WCn+Q1C7YP+yureGt3/+GqpLD9Bszjktuvxutvu1dSMrxxRFP/H0xGFLIzLyGzMxrCId91NaupbJq8fGBq82rrCZoJ5PWMBdrQl7ctn74/X4+WP4Bu4/tpqSyhIAuwH1X3ke/fv1iHZrwDeFGHw3LtqA2+lFVFdPgHBKvnhrrsLqcViUfM2fOZPv27c223XzzzQwaNIi777672TS4559/nssuu4yUFNHs1BqOtHS0BgMVhw5E9Txz+8xlS8UWXP6ePcamJcJhP1VViygte5OamtWAiiRpSE6eSWbGfJzOachyx4/NGGI1sbKmocslH/UVx3jz4fuoO1ZG/uRpXPDjn6NpZy2SE8nH6e4oNRojycnTSU6ejqoqNDQUHh8nspR612bq2czhmr+2u8pqNFRVVfHqklfZWbKTzKRMzs87n34z+5GVlRXr0ISThBsacS3ehBoMIem1WKcM7zZrrMRKq/4i2Gw2hg4d2mybxWLB6XQ2215UVMTKlSv5+OOPOybKHkSWNWQOyKO4cBu1ZUdJzIjeH6H/7vovj0x+JGrH78pUVaWhoZCysrcoP/Y+oVA9AGZzfzIz55OedgUGQ3QTa40kET7rHvF3F199tIQ3H74Pd001I2ZfyMzv/RipA5qgz5Z8nEySZOz24djtw+nX9w58vlLK939CjXcldQ1ftrvKakeprq7mg1UfsLZoLRP6T+CBmx4gJSUlbltmeqJgeTXuL3aihsPIBh32C8ag6YZlzmMlKhVN/vWvf5Gdnc2cOXOicfi4YNbIeEJhLNqOL3rUZ+QYigu3cWDTekZfHL3kw6q3otPE/u4vngQC1ZGaHKVv4PbsAUCjsZKVeT0ZGfOx20fExQVCCQSQdPH1uzt2oIi3Hvkt3gYXYy+fz5Trv9NhP6uWJh/fZDRmkpVyPdn6G8AaoqZmNZVVi6muXn5KldXU1IvIyrqu1YODW6O2tpZXFr3C9uLtDM8Zzu+/+3uSk8XU93jh3XkIb+EhJElCTrDguERMi42Wdicfy5cvP2XbI488wiOPdO876jyLkT0eHwWOM9dqaKsB4yay4j//onDZIgouujwqF7s9NXsoaSjp8ON2Raoaprp6BaVlb1BVtQxVjUx3TkycSGbGfFJS5qDRxKYkfZJWQ00wRNI3Kh+Ga2vRxNGiYUd27+CdRx8k4G1k8vXfYdwVHVvNuK3JB4CkkSCkotVaSU2dS2rqXFQ1TH395qZxIieqrDa4dzAo7/cd/pk7cuQI/3jrH1QGKhnXbxwLb1koFn2LA/7D5TRuKoJQpI1Rn5sipsV2kp5Ty7WDJeq0bAo1RuXYjtR0sgYN4ejuHbhrq7Eldfyd0eLixSw4b0GHH7erUVWV7YW3UVn5GQBGY/bxmhzzMJliv4bIUJuJtXUepiY1n54arq1FE+PF5U44tGUj7/3pEULBADNv+Qkj51zU4edoT/KBRkb1h5ptkiQNCQljSEgYw4D+9+Dx7Gfrth9SWvoaWq2d/v3u7pAEpK6ujo9WfsTy3cuxKBYW/nAhSXHye+tJQi43nnW7UVyNkaWvj6+QrE2247hwLLJRTHrobCL5aIdo1mE4UeFUPf5Ht6PV++tJt6Sfe8durqTkBSorP8NqzWfAgF+TmDAOSYqfux69LBM8zVLy4dpaDH37xiCi5vZ++QUf/eUxVFXhwlvvZPCU6VE5j6IokabwNrZ8KOGzf1otln4UjHqZDRuvobj4OXRaB717/7it4QJw9OhRfvvKbxmWPYyHbnyIjIyeU5U1lkK1Ltyrd6D6g02JhmTQYRk3qFuvEtvViOSjnaJVvEh3fPpxoDE6rStj0sYw7715fDb/s6gcvyuod22laP8f0WptDB/2d0ymrlNfJrI2RGyrnxYuW8Tnz/4VWSNz6R330n/s+KidS5IkVFXlj3/84xn3UY8naaqqnvZLkqSmz+qJ/3/zy2icyoCB77H/wOOsWLme2prhp+wDkRIBN998M9ozzOIJh8ORtWhUmRnDZojEIwoURSFwsBzf7mJUX6SrFFVFNhuwTh2G1i6W9IhnIvlohzyLkd0eH/nWjh8PYE1yApF6Cck5vTv8+AVpBZi0sRnHEA+CQReFhT9DVYPkD/pLXCceNo2MKxTGHoXBzW216eP3WPbSc+gMRi6/6z5yh42M6vkcDge33norwWDwrPudnCTIshxJWkIKoYpGdJmRi9HJCQlELmInb/N6Z3Lk6M/Jzl5JwaiJWK0zm7p9VFUlEAjw+uuvEwgETpt8bCncwr+W/IuAL4Aqqzz6+aP8xPMTJo+b3ME/lZ5HCYVpWLaZcLUbSSOhy07GOmWoSDS6IJF8tEMvo56l1a6oJB9KODIAStZE51cUUkIMSR4SlWPHO1VV2bX7bny+I2Rn30hq6gWxDumshtvMbHR5mJx48riP2BRfV1WVdW+9ypo3/ovBYmHePQ+SOXBQp5y7rTWD1LCC3+3CmJzQwmdkk5LyLzZv+Q6VVX8kPaMPKckzmx4NhSLjR5STukRDoRDPvf0cJfUllLhL+P7o7zNl8hQqKyt56IWH+MP6P7Bq0yru/J4ok95aiqLQuHYHgSPVIIF10hD0WaJ+VFcXP53bXVS0Jl36PZHVbQ2Wjp9NA1Djq6GPo09Ujh3vjhz5N5WVn2OzDWFA//gfdGvSyPiU2K/0oqoqK15+njVv/BezI4Fr73+00xKPdpElaOXPLyFhDMOH/Q2QKSz8KbW1674+3PFxJycnHxs3b2TVkVVQB7+a9SsmTpiILMukpaXx1F1P8b3e3+OA5wBut7sjXlGPoCgKte+upu71lWhTHCRdO42ka6aJxKObEMlHnAo3rW4bnZaPu1bcxezc2VE5djxzubazr+hRNBorQ4c8hSyLu9CWUJQwnz/7VzZ+9C625BSue/APpOR2jeS1rWOynM6pDBnyZxQlxNZtP8Tl2gZEko8wYd5d9C5FRUX4fD4SEhKwhCz069ePYcOGoTupBotGo+HKS67kuV8+h9Pp7JDX1N15vtpJ7X+XYp00lKTrpmEcmBPrkIQOJrpd2kE9zSyEruLKAVeSYupZdxChUMPxcR4B8gc9jtncO9YhtZhJlvCEw1ialjDovEJn4VCQj5/+M3vXriIxI4v59z2MPblnvHfSUi8iPMjNrt0L2LzlZkYX/A+rdSAjpo/gw+0fsu7QOsKhMIqkMCZ3DLfMuyXWIXdp7i93EthfjiE/G+eNs2IdjhBFIvmIU2ZHAgCeulqSe+V2+PF1so6bPrmJNy97s8OPHY8i4zzuxesrJivrW6SlXRzrkFplpM3MVpeXiYmdO7Au6PfxwZ8XcnDLRlJ692X+vQ81vTd7iszMawiGXBQVLWTzlu8wZvRrTBg9gYKRBfS29cblciHLMlarGPTYVieSDuPgXiR9a0aswxE6geh2aYdoltk+cWfZUFUZlePfNPgmLDoLe2r2ROX48ebo0VeoqPg4Us+j/32xDqfVLFoNjVGq+XIm/sZG3l74AAe3bCRzYD7X/PaRHpd4nJCb8316976VQKCCzZu/Q8BfhURkRk1CQgJ2u11UxWwDxeen+qVFyAYdSd+agXnkgFiHJHQS8WmJU7bjyYcrSsmHJEm8MPcF5n8wH3/YH5VzxIuGhp3sK3oYjcbCsKF/RaPp2uM8It190e3ya3TV88bv7uXIrkJyh49i/q9/h9HSs+/s+/a5g+zsG/H6iinc+QuUUEOsQ+rSAqWV1PxvOYlXTxFJRw8kko84ZXeeSD4qonYOWZK5oPcFbK/cHrVzxFoo5GZ74W0oSoBBeQ9jNneNQZKnY5AkfGEFxdOIHKVZUAANNVW8/uACjh0oov/YCVzxq9+iM4rVPCVJYuCA35KedgWexkPs3nMvoZCYvdIW7jWFeNbtJuk7s5HFSrE9kkg+4pQjLVL6vOZodBd/m9ZrGgu/WhjVc8SKqqrs3nMfXu8hMjOuIT39sliH1C7DbSa2NTQSrqtFkxCdMtF1x8p57f67qT5SzODzZ3DpHfegjbPVc2NJkmTy8/9AQuJEPO7dbNv2I8LdvOWwIymKQu1bq0Ajkzhviuiq6sHEbz5OmWx2EjOzOXagiKDPF7XzzM6dTZY1K2rHj6XS0tc4duwDLJaBDBz421iH024OnRZXWCFcW4s2qeOTj6qSw7x6/6+orzjGyAsuYe6Pf46siZ+qqvFClrX07/9rEhwF1Nato3DHz1CUs1deFSJrrtS8tAjL+EFYxw2OdThCjInko50kCZQoTbnNHTYSJRzmwOYNUTk+gEFjwBP0RO34sdLg3s3efQ8hy6bj4zy6Tyl5jcOB/8DBDj1m+f59vPbgAjy1NYyfdy0zbv4RkrgrPSNJ1pI/6BHs9hFUVS1m1657UNXOHRDclXg27cX12UaSbpwlioQJgEg+2i1Nr+NYIDp3PXkTImtB7Fy1NCrHP+GBiQ9wy2fdpz5BKOShsPA2FMXPoLyHsFj6xzqkDqOVQMruhcZmpXFDxySlJTu388bv7sXX4OL8b3+PSdfeGNWZXN2BqqrotFZGjvgXFstAyo+9y969D3Xp2j/RoARD1Ly+HKXBS9J105HjaH0iIbZE8tFOvU0GDjRGp883K28wSZnZHNi0ntry0qicAyDTkslX5V/RGIzOCrqdSVVV9uz5LY2NB8hIv4qMjHmxDqlDDbOa2d7QiGHAADRJTjzrvmzX8Q5sXs/bj9xPwOdj9g9+ythLu9fPK1oUFGRJRqdLYNTIlzAZczhy9GUOHHwi1qHFDffaHdS+vgL73DHYpo6IdThCnBHJRztFc90NSZYZffEVoKqse/N/UTkHgEbW8Pyc57n+o+sJhrt233VZ2ZuUH3sXi2UAeXkPxDqcDufUa6kJRRYdNPTtgy4zA/cXX7TpWLvXrOS9xx5GUcJcfNsvGT5rbkeG2q2pqoosRf58GgypjBr1bwz6NA4deobDxc/FOLrYCjc0Uv3yYiSDDucNM8WKs8JpieQjzg2ZNpOE9Ax2rlpG2b7oFQQ7L+M83rz0TZ4vfD5q54g2t3sve/Y+gCwbGTrkKTQac6xDijp9Tg6G3r1xr1zZqudtW/IZHz31GLKs4fJf3segSVOjFGH3pKgK0kkl7k2mXowc9RI6XSJFRY9ytPS1GEYXO+4vd1L/4ToSr5mKpWBgrMMR4phIPjqASZbxHL8b7WgarY7zv3UzABs+ejcq5zhBp9ExOm00nx78NKrniYZwuPF4PQ8feQMfwGrtvn/4ZCB80tgCXVYWhrxBNCxd1qLnb/jgbRb986/oDEbmLXiAvgVjoxRp93Wi2+VkZlMuffv8HIDdu39NVVXLfh/dQbCilup/L0bSyCRdPwPZIKZnC2cn1nbpAGMcZtbUuZmWZI/K8fuNHYfBbKG4cCtKOBzV6Y9j08eyo3oH/931Xy7pewkOgyNq5+pIe/Y8QGNjEelpV5CRMT/W4UTVEKuJHW4vw21ft+zo0lKRtBpcixZhmzXrtANGVVVlzRv/Zd1br2K02pi34AEy+ud1ZujdhqqqhIJ1VDZspL5+E/X1m3A1bENRToz/UnG5tpKcPD2mcUaboii4PlgLQOK3Z4i6HUKLieSjA+hlmWCUxn0AyLKGPqPGsPuLFRQXbqX3iIKonQtgiHMIg5MG88iXj/Dr8b+O6rk6QlnZ25SVv4XZ3Je8vIe6/UyNNIOO7W7vKdu1TieWsWNp+PRTbHPnNvs5qIrCsn8/x+ZPPsCSmMT8ex8iOad3J0bdtamqgsezrynR2Fr+JXblKOaTrrVGYzYOR8Hxr1HYrENiF3An8B8qw718O7Y5o9BniumzQuuI5KOD2LQa6oMhHLro/EiHTJ3J7i9WsOnj96KefECklLRW1qKqalxfzD2eInbv+S2ybGDo0L+i1Uav7HhXoElIwDJlCq6PP8Z+4YVIsowSDvP5s39lx4rF2FPSuPq+h0lIz4h1qHEtFHLjcm2lrn4T9fUbcbm2EDppLRdfQE+vxOFkJI1tSjYMhrQYRtx5wg2N1H+4Do3ThvO7c2IdjtBFieSjg4x1WFhS7WJOcnS6KXKHjyIltw8Ht2yk4tABUnv3jcp5TpZoTCSoBNFr9FE/V1uEw97j4zy8DMp7GJt1UKxD6jQSkeJ28mkSQ43Vim36dFwffYx51kw++fsT7PtyDUlZvZh/3++wJSV3fsBxTFVVfL6S44lG5Mvt3gN8XTRMp3OSkjz765YNb5jBycMw67r/oOYTFEXB9eFaVH+IhHlTxLgOoV1E8tFBNFJk7HtYVdFEoaVAkiTGXj6fj596jPXvv8XFP7urw8/xTaPTRrOkeAkX9rkw6udqi717H8Lj2Uta6iVkZl4X63A61UCLkT0eH/nW01dulc1mjFOn8NaCOzhadoTUPv246t6HMNu7xhieaAqH/TS4C5sSjfr6TQQCVSftIWG15kWSDHsk2TCZcpq1AEr+jXHdItiRFEWhYfEmQhV12OeMRpcanXWFhJ5FJB8daGKClbV1biYn2qJy/Lzxk/ni1X+zZ80qJl5zA4npmVE5zwmBcIApWVOieo62Ki9/n9Ky1zGZchk06OEecyE4oZdRz+Jq1xmTD3+jh7cf/z2lZUdIT01n3t33Y+qhiYffX0m1dyWN+/YcHxi6A1UNND2u0VhJSprydauGfQRa7dk/w4p66myX7qhh5VaCR6qxTB6CYc6YWIcjdCMi+ehAFq2GhlD4jM3h7SVrNJx3xdUs+ufTLHn+71x1b3QHV45JG8NPl/6UZ2c/G7VztEVj40F277kPSdIzbOhfz3mh6Gka6+t465H7qTi0n94jR3Pp7XfjXboMw8wZyKbus8bN6ahqGLd7T1OLRl39Jny+4ytDV0f+MZlymxKNBMdoLJb+SFLrZpCpqorcjSsVhOoaqP/wS4xDckj61oxYhyN0QyL56GATE6x8Ve9hfEJ0qvoNmz6HwuWLObxtM7tWL2fwlOhN5ZMlmTWla6J2/LYIh/1sL7yNcNhD3sAHsdm694yCc/nmgOCG6ireePg+akuPMHD8ZC667RdotDp0F12I65NPsE6disbafSpOBoMuXK7NTeM1XK6thMNfL5Qoy3ocjjFYw4Nx9pmIwzEKvb79Y14UFOiGjW1KKEz9B2tBVUm8dhpylAbQC4J4Z3WwEl+AFH30fqySLDPnh7fx8t23s/Rf/yC930CSMrOici6NrOH2gtujcuy22lf0MG73LlJTLiQr64ZYhxNTfU0GDnj99DMbAagtL+XNh+/DVVnB0Omzmf3DnyLLkTt6SZaxX3QRDZ99hmX8eDQJCTGMvG1UVcXrPURd/de1NTyeIuDrae4GfRrOpPObWjZstsHIsh7f3lqMKR03VkFRlW7X8uFaspHQsXrsF45BmxidmkWCcIJIPjqQN6xw1B/kgijNeDkhuVcuU2/8Hste/CfvPfY7rvvdY5is0el6mJM7h62VWxmREvuFoY4d+4ijR1/BZMwhP39hjxvn8U19THqW1DTQz2yksvgQb/3+N3jqahl98eVMvfH7p/x8JEnCdsEFNCxahHn0aLROZ4wib5lw2IvLtT2SaLg2UV+/mWCwpulxSdJgsw0+aWDoaIzGzE55X5y8tktX51q8kVCVC/PYAdhnjo51OEIPIZKPDrSytoGZUapy+k2j5l5KxaED7Fi+mPcee5hr7n+k6S63I2VZs1havDTmyUdj4yF27b4XSdIxdOhfxDgPaLrIlu3bw9sL78fncTNh/reYMP/6M16AJUnCPmcODUuXYhwyFF1aameG3CKBQBXbC39Gff1GVDXUtF2rdeB0Tmtq1bDbhsesrotKfNe/aamGlVvR2E3YZ4mkQ+hc7UrdH330USRJ4uc//3mz7WvXrmXGjBlYLBbsdjvnn38+Xu+pFRm7k7pgCItGRit3zh8kSZKaFgM7unsHVcWHo3Iejayhf2L/qBy7pcJhP4WFPyMcdjOg/z3Y7cNjGk88qTx0kDd+92t8HjfTbvoBE6/+VosuirYZM/Dv3kWwtLQTomydxsZD1NV9iUZjISPjavIHLWT8uM84f8oGRo54nj69byUpcUKPLyjXXo1b9qF4/VjOGxzrUIQeqM0tH+vXr+fZZ59l+PDmF4K1a9cyd+5cFixYwF//+le0Wi1bt27t9jX/19a5mRvl7pYTQsEgq1/9Nxs/fAeAgeMmkRilcR8AwXAwasduiaKihTS4d5CSMofs7O/ENJZ4sn/jlxS+8DxavZn5N/+QYdNbV23SOnUq7i++QA2F0OfkRCnK1rPZBiNJGvT6FAbnPxrrcJpxBVx8WfYlli6e+PgOlOI/UE7ivPicSi90f21KPtxuNzfccAPPPfccDz/8cLPH7rjjDn72s59xzz33NG3Ly+vei1cd8wdJ1es6pRm2+mgJHz35ByqLD2FNcjL3x3eQO3xk1M5X6i4lzRK7stHHKj7hyNGXMRqzyR/0aLdo6u4Iu1Yv55Nn/oxTknH+5G6GTZ7QpuNYJ03C8+VXqKEwhr59OjjKttFozFitg2lo2E4wWIdOlxDTeE6eUbSlYgszc2Z26fEewYpaPGt24vz2rFiHIvRgbfoE3XrrrVx88cXMmtX8zVtRUcGXX35JamoqEydOJC0tjalTp7J69eozHsvv9+NyuZp9dTVbGhoZ7Yj+ndCR3Tv4329+SWXxIQZOmMJNjz0d1cQD4JDrEAMSBkT1HGfi9Raza9c9SJKWoUP+gk7XM4tkfdPWRR/z8dN/QqPVceWvfkNWfvumG1vGnUe4tgb/vn0dFGH7JTgiYxDq6zfHLIaKxgoWH17MqqOrWHlkJSuPrEQrabt04hGqa8D1yQYSRe0OIcZa3fLx6quvsmnTJtavX3/KYwcOHADggQce4PHHH2fkyJH8+9//ZubMmRQWFjJgwKkXsYULF/Lggw+2IfT44A0rGDuhS6lk53beXvgAoWCAaTf9gIKLLuuUVoBEQyL1gXqSTZ27Hoii+NneNM7jXhyOkZ16/nj11XtvsuqVF9GbTFx59/1k5w9lf3X7E3bz6NF4t2zBt2sXxvz8Doi0fRwJoyk58iJ19Rs7bVl6RVWo8dXgNDpRUdlQvoGL+l7UKefuLP4DpZjHDuj23eBC/GvVO7CkpITbb7+d//73vxiNxlMeV5TIQkw/+tGPuPnmmxk1ahRPPPEEeXl5/Otf/zrtMRcsWEB9fX3TV0lJSRteRuysrXMzMUoFxU44dnA/7/zhIULBABfeeiejL76807ofUswpHPMc65Rznayo6I80NGwnOXkmvXp9r9PPH29UVWXV/15i1SsvYrLZuea3C8nOHwpAml5Lub/943JMI0eihsJ4txe2+1jt9XXLx8aOOaAEqqKe8WF/2M/HBz+morGCL0q/YEXJCgrSor96dGcLVTWgTRNrswix16qWj40bN1JRUUFBwdcfynA4zMqVK3n66afZs2cPAIMHNx89nZ+fT3Fx8WmPaTAYMBgMrY07boRUFV0UZ7g0uup577GHCfq8zP7hbVGtaHo6yaZkdlTt6NRzVlevpOTIixgMGQzO/2OPH+ehKgpLX3yWLZ99hDUxifn3/R5ndq+mxwdbTayoaSC9A1YZNQ0bim/3brxbtmAaObLdx2srgyENozELl2srihJEltv32iSNBGEVjn9WVVXFE/Swq2YXvpAPb8jLBbkXoNN075ValQYvOqfovhRir1XJx8yZM9m+fXuzbTfffDODBg3i7rvvpm/fvmRmZjYlISfs3buXCy+Mz5VR22N/o4/+5lNbgDqKqqosfu4ZGqorGX3x5QyfeUHUznW2GMJquFPPWVf3FQB9+9we88GGsaaEw3z69yfZtWoZjrR0rr7vYRyp6c320UjSSYu/t59x0CD8+/bRuGED5jGxW0zM4RjNsWPv0+DeicPezjozWhk1rCDpZLZXbmd//X4yLBkMTxmOSdu917sRhHjUquTDZrMxdOjQZtssFgtOp7Np+1133cX999/PiBEjGDlyJC+99BK7d+/mzTff7Lio48SBRj+zozi9dvealez7ag0puX2Y8q3vRu08ZyNJElq5c2vR2WyR91Jj44FOPW+8CQUCfPiXP7J/wzqc2TnMv+9hrIlJnXJuw4AB+A8cxLPuSyzjx3XKOb8p4XjyUV+3sd3Jh6SRKardT2mojBx7Dlf0v6JjghQEoU06/Kry85//HJ/Pxx133EFNTQ0jRoxg0aJF9OvXr6NP1a0FA35W/vcFJFlm7k/uQKONTXNwvb8eh6Fzm2kdx/v76+o3dep540nA5+W9xx6muHAr6f0GMG/Bg5hsZ66em6TTUBUIkdyB6woZ+vZB0mlxf/EF1kmTOuy4LeVoGvexCWjfuJ9d7t1oTXqm5Uxrf2BdlKIooJ553IsgdKZ2/6Vavnz5KdvuueeeZnU+uqMjvgDZRn3Ujr/ls49wV1cxfNZcUnv3jdp5zuWw6zC97b079ZwGQwomYw4NDdtQFD+y3HXHBLWFz+3m7T88QNne3WQPHsqVv/otepP5rM8ZZjXzRV0D0zq4vL++Vy8kjQb3ypVYzz+/Q499LlbrQDQaK3X1G09Zvbc1wkqY8kAFM1N69vRS79YiDP0zYh2GIADtLK/ek+31+MizRGe8RygYZMMHb6PR6Zhw1fVROUdLlXnKOr3lA8DhKEBRAjQ0dO5g11jz1NXy+oP3ULZ3N30LxjJvwYPnTDwUVWVNnRuHNjrdY7rMTAx5g2hYujQqxz+TUMiFLOsJBqtR1UCbjqGoCm8Xvc3k9Emo4Y4cGdP1BIrKMA4XLdBCfBDJRxupgBylWRhFX62hsb6O/MnTsSbFZuVRVVVZVryMkSkjY3J+R0LP63pxVVXw2gN3U1l8iLyJ53PZL36NTn/2Vp9N9R4+q6pntN3MKPvZk5T20KWlYhoxAtfnn6N2QtO9qqrs2HkXwWANvbK/2+bWL3/YT4IhAaPBGJnt0sOJ+h5CvBDvxDi0Y8USAIbP6vzZLQC+kI8PD3zI6PTRMSut3uF1HuJcTelRXv3t3dSWlTJ85lwuuu0XaM7SklHU6OPjyjoyjDouTEnAqu34FY2/Set0YjnvPBo+/TTqCUhxyfNUVy/Dbh9Jv353tfk4q4+uZkavGaCRUXtw8hF2e5EMYhFzIX6I5KMNQoqKNkqtHg01VRzetoWkrF6k9xsYlXOcyxdHv+CiPhdh13fs+IHWsFgGRPr76zZ2yp12LFUcOsBrD9xNQ3UlYy6dx6wf3Iosnz6ZqAwE+aiyjpCqclFKAhmG6I07Oh1NQgKWKVNwffwxqhKdboz6+s3s3/8YWq2doUP+0uYaH+vL15Nrz0Uja5A0Uo/udnEt2oht1uhYhyEITUQq3AYlvgA5URpsuu/LtaiqwuDzZ3R6ca0DdQc4UH+AfGc+mjNc/DqLJMk4HKOoqVmF13sYs7l3TOOJlqN7dvHOHx7A7/Ew6dobGXflNaf9vTeGFVbWNODUa7ko2RHTwmsaqxXbjBm4Pv4E+9wLkDpwrEkwWE/hjttR1RCD8/+AyZTdquerqsqX5V/iDXoZkjyEVHMqEJlqS6h7J7FnowZCaKJYk0gQWkskH21Q7AswKUol1Y/ujgyw7DOyc+5SgkqQ9eXr8Yf89Evox6zc+FnpMsExmpqaVdTXb+qSyYeqqvj9ZdTVb6S+fhNu925yen2PlJTZABzetoV3H/8dIb+fGTf/iFFzLz3lGGFVZWVNAwCzk+1o4qTaq2wyYZs9C9cnn0YSEF37p4KrqsrOXb/C5ztKr+zvkpIyp9XHeKfoHWblzjq11a4Ht3x4Nu3FMDAz1mEIQjMi+WiDsKqijVJJ9fL9+9AaDCTn5Ebl+CfbXbObkoYSJmdNjssqj1/X+9hIRsa8GEdzbooSoMG9i/r6TU1ffn95s33q6zczYvg/qTmg46Mn/4ASVpj7kzsYMnXmKcfbUO+hKhBiSqIVSyeM6Wgt2WDAPvcCXJ9+im3OHOR2LpNQcuRFqqoWY7MNo3//u1v9/FpfLf0T+p+2u1CSpcgo8R7Iv/coSdd17rIMgnAuIvmII6FAAFdVBam5fc/Y599eqqqyrWob1d5qBiYOZHbu7KicpyM4HCORJE3cDjoNBKqpr9/clGi4jtclOUGjsZCYOBGHo4AERwHBkIudO3/Blq0/Yt/7WYCVS++8hwHnTWx23L0eH0WNPkbbLYxxWDr5VbWOpNNhv+giXB9/gm3mDGRz22bcuFzbKCr6AxqNlWFDn0KWW9+tuatmF2PSYlcOPh75D5WhSbLFOgxBOIVIPuKIt8EFqoo1KXoltJcWL2VE6ghGpLRzrYxOoNGYsVrzaWgoJBh0odPFbgCsqip4PPuaEo26+k14vYea7WM09iLBUYDj+JfFMhD5G6XpD23dgEf7H/rOPUxu6h8YUPB14nHMH2Sjy0N/s5GLUhI64VV1DEmjwX7xRbg++QTr1KlorK3rkgwGXWwv/BmqGiQ//wlMppw2xREIB9BrOncAbrxzf7GTxOtFq4cQf0TyEUd8HjcABkt0xpMc8xwjzZJGsik5KsePBoejgIaGQupdm0h2Tuu084ZCDbhc26ir30R9/UZcri2EQg1Nj0uSHod91PFEYzQOxygMhtQzHk9VVb569w2+eHUj6aNySD+vmGOeR+nVOApVn8PK2gZS9LoulXScTJJl7BddRMOnn2KZMAFNQkKLnqeqKrt2L8DnKyEr69ukpbZ9AUpZEpP3TubbdQh9r2RR20OISyL5aINoD/mL1vETjAmsP7ae/gn9MWq7xsj3BMdojhz5N/V1G6OWfKiqis9XcjzR2HR8cOgeOGmtWL0+mZSUCU2tGjbrUDSalo1xUFWVVa+8yPr338JkdzD7uqfw8AlFB57k/zYuJG/AAuak9Y6bwaRtJUkStrlzaVi8GHNBAVrnuQvkHTn6HyorP8VqHcyA/vd2QpQ9h2dDEc4b42cAuSCcTCQfceRENcuAzxeV4xs0Bi7sfSGfH/6ciZkTY1I2vbVOHnTaUcJhPw3uwmYDQwOBqpP2kLFa85oSjQRHAUZjrzZNb1WUMEue/zvbFn+K1ZnM1fc9TGJGFgfrv0NJipH+lY9jP3SAcNKraPRdp0XqTCRJwj57Ng1Ll2EcMgRd2plbg1wNhezb9wgajYVhQ59qcTJ3Jg6Dg5VHViJLMhpJg1FrxB1wk+/M71KtfR2h/vMNWMbnxToMQTgjkXzEEfPxpmp3bXXUzqGRNcztPZelJUsZ6hwaswqmLWU0ZmA0ZOJybUNRgm0qOOX3VxwfGLrx+MDQHc3WCtForCQlTcHhGE2CowC7fThabfsH6YVDIT792xPs/mIFiRmZzP/1w5Sabayrqmesw8J5Q7/H7t1FlJa9zubNN5Gb+/9wOqei08V/UnguthnTca9cCeEQusxTp3mGQg0UFt6GqgYYNOiPmM192n3Ok8cxBZUggXAAi87CpmOb2Fm9kzHqkHafoysIllejeHwYB/SKdSiCcEYi+WiDaM3Y0xtNWBKTqC072q5VPM9FkiRm5sxk9dHVqKikW9Kjcp6O4nAUcKziQ9zuXdjtw8+6r6KE8Hj2NhsY6vOVNNvHZOr9jYGhA5A6eLxAMODnwyce5cCm9aTk9GbSXfezGh0DJanZuI5Bgx4mFPZQUfERO3begSRpSHCMJTl5JsnJMzGboz/lOlqs55+PZ80a1FAIfc7Xg0gj4zx+jddbTGbmdaSnnVrfpL10sg7d8US1IK2A9eXraQx7id7qN/HD9fkmEr996tRtQYgnIvloA40kRUqsR6HWR2rvvhzcvIHasqMkZbauumNrTc6azGeHPiPVnBrXg/UcCaM5VvEhdfUbT0k+gkEXLtfmpvEaLtdWwmFP0+OybCDBMbYp0XA4RqHXR3exvoC3kXcfe5iSHdtIHDQE+/fvoN5g5qLTTJuVJA1Dh/yFuuwbqapaQlXVEmrr1lFbt459Rb/HbO5PSvJMklNm4rBHph53JZaJE2ncsIHAoUNIej3GwYMpa/iQioqPsFoHMXDAb5rtr6gK26u2U+ouJcmYhNPoJNmUjN1gb9d7dGjyUD7b/wFzQ5dFdbxTUAmypWILg52Dseg6f5p03YfrsEzKF4NMhbgnko826GXUc8QfoLepfX3Up5OdP5SDmzdQXLgt6skHwKTMSawvX8+4jHFRP1dbfb3I3CYandOaKobW12/C49nXbF+DPg2nc+pJA0Pz21Qzoq287gbeXng/pfuL8EyZw4j532JGmvOsKyBLkkRiwlgSE8YyoP89NDYepPJ4IlJXt4HDxUUcLn4WnS6JZOd0kpNnkpQ0Ga02vmuAnGAeE6m9ofj9VG/7mL0NDyJjoK/3JsKllfjTnXxZ9iXLjyxnRckKqn2ndjtqJS1Jpq+TEafJ2ez/yaZknEYnTpMTu95+SquhSWtidvIMFhcv5oLeFzS1inQUX8jH2/ve5slNT+INefl/I/4ft468tUPPcS7utTvQJlow9ov+3w1BaC+RfLRBL6OetXXuqCQffQvGsuqVF9mzdiUj51zU4cf/JqveSlgNU+4pj9vuF4slMnCuouJjKio+btouSRpstqEnDQwdjcGQEbN1T9y1Nbz5+9+wNQgJMy7lFzfeiM3U+rtss7kPuTnfJzfn+wSDtVRVr6CqagnV1SspK3+LsvK3kCQ9SUkTSHbOJDl5BkZjRhReUcdSNEGKws+gEqJX//tY6dWwZeX9HN23iaASBCDdZmJ0wUwGpQyh1l9LlbeKGm8NVd4qqn3V7KrZdc7z6GTdKcmJ0+ikf00W9DXw353/ZXjKcArSCtr9mhoCDby25zVe3vkyNb6apu1V3qqzPKvj+fYfIVRZR8Jlkzr1vILQViL5aAOdLBGM0kqryb1yScntw5GdhdSWl5KYHv01GSZmTmTlkZUAcZmAnFyoy24fSUryTBzHB4ZqNPHRi19fcYynn/ozxVoL0/tlc/X3bkbTAQuu6XSJZKRfQUb6FShKgNq6r5q6Z6qrV1BdvYI9e3+LzTrk+DiRGdhsQ2O68NzpqKrKhu130Nh4kL2hFO5Y9hjq8dFTaUPSmNZrGtN7TadA34/w3v1QGwKIdNWMGIzGERmEG1SC1HhrqPZVRxISbzXVvmqqvdVNCcqJ7eWe5qXtC9z5bDoaSV6yrdk8NOkhxqaPbdPrqfHV8J+d/+HV3a/SEGxAL+u5Lu86xmeO5+fLfk4wHGzrj6rVgtX1eNbuxvltMa1W6DokNc7WK3e5XDgcDurr67HbY1fR8lwWV7uY5YxOfFsXfcLi/3uG4TPnMvuHP43KOU5nS8UW3EF30/eKqjA0eShJxuhVXG2pxsbDmEzZHTPmwVsLz54PkgZGfgtGXAcJbauqCVB46BDP/edlrMVFTD9vHDO/9/+QotznrqoqHs9eKqsWU1W1BJdra9NjBkM6yckzSHbOIDFx4ilTWEMhD4FAFYFAJYFAFf5AZeT//srj26tAkhk27BmMho5JRt/e+Asc9e9SFpT48zEj/RMHNyUcg5IGnTFZUvx+fDt3ojR8XeBNn5uLLifnnAlWIBygxlfTlIwEi1wccJax6dgmvij9AoDZubO5c/SdZNta1lVR7innpR0v8ebeN/GFfVh0Fq7Nu5YbB99IsimZHdU7uO7D65g3YB4PTnywhT+dtguWVeFatJnEb88U4zyEmGvN9VskH220uNrFzCRbVO4wQ4EA/3fbLXgbGvjO48+QlJnV4edoiRPrwNT76wEYkDCADGv8N++f0+f3wZq/Nt/WewqMvAEGXwb6lo2laAiF+WD3Pnb8+58kHd7LeVdczeTrbopJq4PfX0FV9TKqqpZSU7MaRYnUitFozDjsBYQVb1OyEQ43tuiY6elXMGTwn9odm9u9hy/XX0EgHOBPx4xM63c9vx736zb9nFRVJXDoEMGSr2cwaRwOjPn5SPqzj+3x7a1F09/Kpwc/xagx8retf6OorgidrOOmwTfxg+E/OOMg0cOuw7xQ+ALv7X+PkBIiwZDAt/O/zXWDrmtWL2fTsU1859PvcG3etdw3/r5Wv77W8Bcfw71yO4nfmiESDyEuiOSjExzy+gkqKgMs0Rk5v23JZyz651/JHT6Kq+59KC6a0XdV76K4oZjpvaZ33TU06krgr6PBYIVbFsHeT2HLK3CsMPK43gqDL4+0iORMhNP8UQ8qKitqG3AdOcyRJ35H0NvIlG99l/Mun9/JL+b0wmEvNbVrjnfPLCUQqARAlk0YDCno9cno9Sno9SkYTvzfkIJBH3lMq7Xz1frL8HoPM3bMu9jtw1odg6qquFybKS19g2MVHxMOu7Fk3crdW96jxlfDZf0u4/4J93fI+yhUW4t/1y7U0PGuGp0OY37+KSXey3ccYrN5F7NyZqHT6AgpId7c+ybPbHmGOn8dTqOT2wtu5/L+lzfNrNlTs4fntz/PZ4c/Q1EVUk2pfGfId5g/cD5m3aldfh8e+JAFqxZwe8HtfH/Y99v92s7Et7+UxvV7xGq1QlwRyUcnUFWVxdUuZidHpyCUqij87zd3UVa0hxnf+3+MuuCSqJyntYJKkOUly+N6Ndyzeuf/wdb/wYV/hHE/+np72bZIErL9dWg8PtsiIRdGXB/plknqg6qqrK3z0BAO07ukiE///AihYICZ3/txpwwObgtVVfD7y9FqHa2aHVNR8RnbC39CQsI4Ckb9t8XJr99/jLLydykre5PGxgMAaLUJ5ObcQu/eP+FIwxFuXXIrB+oPMDptNE9Oe5IEY0JbXtoZKYEA/p07CbsiCzUC6HJyqHSHqUpzMzJ1ZLP96/31/GPrP3h196uE1BD5SfncOPhGPjv0GSuOrAAiY0RuGXYLl/W77KwJ01ObnuK57c/x5PQnmZkTnVobvj2H8W47ROLVU6NyfEFoK5F8dJLPq+qZE6XkA6C2vJT/3HM74WCQa+5fSObA/KidqzX21+0npITIS+pi5ZvLt8M/pkBib7j1K9Ce5iISCkDRokgisvdTUCJ3057sCewfOI+sUVdTvXMnH/3lMVRV4cKf3EH+lO5396mqKps2XU9d/XqGD/sHKSlnTjYVJUBV1VJKy96kunoFkTVxZJzO88nImE9K8gxk+etxJ66Ai18u/yVry9aSY8vhmZnP0NvRO6qvZc/OVezbvpWp6UORJRnZbsc4ZAjySV01B+oP8KcNf2oafA3QP6E/Pxj2A+b0noNWPvcA4tuW3sbykuW8f8X79HG0v2rrNyk+PxVPfkjqzy5GNneN9ZmEnkMkH51kl9uLVauhlzF6XRB71q7mwycfxWi1cd2Df8SZHR8lk1ceWcn52efHOozWeXke7F8C8/8FQ6869/6eKmo3v4q85RUcVTsAUGQDu2oT2OXOYOQPH6X/2AlRDjp2XK5tbF53OUnhVIak/BC5qghqDkaSt15jcScmUupeTXnF+wSDtUBkmnBG+nzSM64462DVoBJk4ZcLeWPvG9j1dp6c/mSbZ56cy7LiZWTbsulVmYxxYCIQ6apxL1mCcehQjIMGNdv/i6NfsKR4CVOypjC119QWFzcLK2GmvDYFjaRhxbUrola4L1TromH5NtRACH1OCtYJPaNsvBD/RPLRiRZV1Uet6+WEDR+8zYr//AuTzc6Vd99PxoDYtzisPrqayVmTYx1Gy+1fBi9fAZkF8P0lpx3LcbL6YIjVdW6yjXpG2MxQXsixd3+H9cgSLNrj0ygdvb7ulnH2i/5riCZvLVTugYpdkX8rj//bUHbWp/n1Mi6HESVzBOaB12IdcC2SvmXTn1VV5d87/82fNvwJjazht+N/y5UDruyIV9PM54c+Z07vOfj21jYlHwDuVauwTJrUYTOTtlVu44aPb+CC3hfw+NTHO+SY5+ItPIC38DCyxYh97lhknaieIMROa67f4p3aTioQVtWoLoc+5tJ5KIrCqlde5PWH7uWSn/+KfqPjtyJp3FEUWPTbyP9nP3TWxCOgKCyvacCskbko2YEkSaiqyrrV21mzzIPZMoNrb5xDUsUK2PMJrPxj5CtnQmSQ6uArwBjHSXNjTfPk4kSy4S4/dV+Dg3DWKI4pe/BazcjpIyn3b8PU6MPhCuJstGCtd5NS2QiVa2HrWpB/CenDIPs8yB4LvcZGxs6c5vMhSRLfGfIdetl6cc+qe/jtmt9S3FDMbaNu69BWgzOO0VDVDp0S/cnBTwCYkjWlw455LqahfTEN7Uuwup66t1cj6TQ4Lp0gkhAh7omWj3Zyh8JsdjUyJan9q6Cey85Vy/js738BVK594NGYjgHpUi0f296At78PAy6AG14/7S6qqvJFnZvGsMLUJBuG4xclVVVZ8fLzbPzoXcyOBOb/+nek5B7vy2+sgcK3YMt/oXRzZJvWBPmXRhKRPueDHKO1WBproHL3qS0Z7mOn7mt0QEo+pA6ClJO+bOkgSRQV/ZHDxc8CYDBkkJExj4z0qyKL3inhyHmOrIeS9ZF/q/Y0P749G77z/llbh3ZW7+S2JbdR4a1gdu5sHpn8SIetwbKseBnTc6af2vKxciXW8zum69AX8jH7zdkEwgGWXbPstDNhOkOorgHXJ+vRJFmxzR4jpuAKnUq0fHQiq1aDJ6xEdRXaEwZPmY5Wr+eDPy/kgyf/wI2P/gWzvesvvx5VIT8sfQgkGWY9cNpdtjc0UuwLMDHBSuI37hh3rV7Oxo/eRdZomiceAOYkOO8Hka+KXZFBqttei8yY2f462LMiXTIjvgXJ/aP3GlUVdr4Lh9ccTzh2g6fi1P2MCZEWmpS8SLKRkgep+WBNO23LxAl9+tyGVufAZhtCUuKE5oXeZA2kDYl8jf5uZJu3Fo5shC//ERm866mIJClnMdg5mP9e/F9uW3obiw4votxTzlMzniLZlNzqH8fJGgINp01i1GCwQxPDN/a+QZ2/jmvzro1Z4gGgTbCRdP0M/MXHqP3PUixj+2PM7x2zeAThTETLRweoCYbY6/ExPsHaKedb/vLzbPzwHXKHj2LeggeQY3B33WVaPtY+A5/dCyO/DVc80+yhw14/hW4vQ60mcs+wTk/1kWLeePg+PLU1JGZkMudHPyM7f+iZzxcOwf6lsPUV2P0RhAOR7dnnRVpDhlwJpoQOenGApwre+yns/eTrbabE5snFiWTDmnrWJKNDHd0IL10GwUa45t+R1qAWaAw2cvfKu1l+ZDkZlgz+NvNv9E9se+KmqAofH/yYS/pe0qzlw7drFxqnE11qapuPfUK9v57L3r2MhkADH8/7OK6WKHAt2Ui41oPjiknI2q61IrLQ9YgBpzHwSWUds50OtHL0/7iHQyHe+N29HN29k2EzL2D2D37a6UXIukTy4a2Dp0ZC0Au3bQJHpFJsbTDE2jo3vYx6htnOfZfqc7tZ8Z/nKVy2CICRF1zMlG99F73RdPYnNtbAjrdhy//g6IbINq0RBl0cSUT6Tm/f3ff+pZG6Je5jkDkKZvwG0oZ2bpJxOpV74V8XgLcGLvsrFNzUqqc3BhuZ9/48jrqPMid3Dn+a1r4qq6uOrGJK9pRmyUdHdrncu+pePjjwATcPuZk7x9zZIcfsSMFqF66PvsI8pj+mwb1jHY7QjbXm+i06BDvItCQ7S2tcnXIujVbLpXcsIDEjk+1LPmPFy88TZzlkfFj9RKQLYPyPwZGFX1H4vKqenW4vFyY7WpR4ABitVi74f7dz1b0PYUtOYctnH/HSL2/l0LbNZ3+iOQnGfh9+sCRSV2TSzyOtEoVvwX+ugieGwKL7I2MxWiPkh89+DS9fCe4KmHwHfO9z6D8TbGfvQom6+iORWUXeGpj1YKsTj2JXMdd9dB1H3UfJsmZxy7Bb2h1Sti2b/XX7232c01lTuoYPDnxAb3tvfjLyJ1E5R3vpnHacN80iWFZN3YfrYh2OIAAi+egwJo2MXfv/27vv+Kaq94Hjn5vVdC86gBZKWV2ULXuXDQ5wMB0MFcWtX8WtPxW3qCAqS2U6UIbsvTcUSqHsQimU7t0mTXJ/fwQqo0BHRsd5v8yrmNzcc3qb5D459znPUZKss81qls4enjz49ke4evtwYMUS1s+chuku19VrlKyL5pwDRy/kTi+yLT2HLek5dPdypZNn+dbkCWreise/nEbzPgPJTklm8cfvsObHbynMy737k32aQu8P4KVYGLXYXGekIAN2TIFp98CMXrBvpvm+O0k5CTOjYNdUcK1jTuSMer/kgmm2lpdmDoiyE6Hj89D5xTLv4ofDP3Au6xyDggfx1+C/CPMOq1CXsvXZnM08i6PqLqNU5XTwykEAnmnxjMUSZK3FrVdrHCPqk/bLWgzZpXjNCoIVVSj4+PTTT5EkiRdffLH4vu7duyNJ0g23p59+uqL9rBLae7iwMzPXZqMQbrV8GfbBZ3j41+bI+tWs/P4rjFfXt6jxNn0ChkIS273AqlyIdHWkTy13NBXM/tc4OhE1dgIPvzcZD//aHN20jl9feYbzR6JLtwOFEhpFmQudvXICBk0x54Mk7ocVr8CXTeCPx+DkWnP+yDWyDAd+Ma/Gm3TEnEMxYYd5Ro2FFBYZWXHkMsk5hWV/si4H5j8IqSfN+TW9PyxXH6KTo9EqtXzY6UNcNBXLoTqWdozY1Fh61utJHZc6xfcbc/NQOFomGMkrygPAU+t5ly0rB4eg2niO7EnW0t0Unrlo7+4INVi5P4n37dvHTz/9RGRk5C2PjR8/nsuXLxffPv/88wp1sirp6uXKloycu29oIW4+vgz74HN86jfgxM6t/Pl/b5KTnmqz9iulK7HI0QvIdw3A1GYsA3w8cLdw3YPAsGY8+vn3tB70AHmZmfw75VNMxjKOPDl6QJsnYNw6mLgfurwCzj7mmSsLHoJvwswr8Cbsgz9Gw/IXzJdUBn8LD881X9axkNPJuWw5mULfcD/iLudwOrkM34wNOlg0Ei4dhKYDzf0rx8hSSn4KibmJhHmHoVaoy/z8m8VnxdPGv80to1y6uOM4hFZsROWapDxzfZQZR2bwy9FfOJt51iL7tSaFWoX36CgKYuLJO3jS3t0RaqhyBR+5ubmMHDmSGTNm4Ol5a8Tv5OSEv79/8a0qJY5WlJdahZdaxam8cnx7LCdnD08efm8y9Zq1IDHuGHNff4EzB/ZatU0J+6+yW5I0vYHklW8hIePU5wMCXaxXf0XtoKX76LE0bt+Jwrxcks9VIK+gVmPo9S68GAOjl0Czh6EwG3Z+D7Oi4Phy8I+EJ7eYp7RaKK9DlmU2xl1BZzDSN9wflVJB1yY+5OkMHDh/l0tAYJ5C+/d4OLcF6nc2j+goyxfoHU45DHDLwm/lFVU/ii0JW7iUe+mG+035+ShdSr/I3p10qNMBV7Ure5P28tWBr7hv6X08vPxh5h6bS3phukXasBbP+ztjTM8hZ8the3dFqIHKFXw8++yzDBw4kKioqBIfnz9/PrVq1SIiIoJJkyaRn59/233pdDqys7NvuFV1ka5OnMnXkWewXQ6G1tmFoW9+QIcHR1CQk82Szz9k+deT0RcWWKU9mcqV4FpoNLEmNYvLcRvwPb8JareA8CE2abteuHn070LskYrvTKGEhj1g6Ax49aR5tkjjvtD1NRi3HnyaVLyNq1JydKyIuUzbIC/C69xYL6Z5oAdezho2nSihXsg1sgwfesGxpebAaPhCUJc/7yE6ORqASJ9bR1PLQ6PU0NqvNakF1hsJfLjpw2wfvp2l9y/ljXveoJVvK46nH+fzfZ/Tb3E/vtr/FWkFaVZrv6LcoloDkLsjxs49EWqaMgcfixYt4uDBg0yePLnEx0eMGMG8efPYtGkTkyZNYu7cuYwaNeq2+5s8eTLu7u7Ft8DAyrFwWkX1qeXGmrRs9CaTzdpUKJR0fGgEwz/8HK86AZzcs4Pzd5uRUcWZZJkt6Tlsy8ihp6cLEbuvvi7vUkbdkgKvBh8Jlgg+rqd1M88WGfkH9HwbVCXXIimPA+fTOZ2cy6DIOrhqS77E0aCWM5F13Vl++BIGYwmv483XfQa4+IE+r0J9upbjsfrcavKL8vn37L/FAUl5nc06S7B7cPH/WyMfSyEpCHYPZmToSH7t/yurhqzimebPoFFq+CX2F/r/3Z/p0dPRX6v5Usm4dmuOMV9H3r7j9u6KUIOUqc5HQkICbdq0Yd26dcW5Ht27d6dFixZMmTKlxOds3LiRXr16cfr0aRo2vLW8sk6nQ6fTFf9/dnY2gYGBVa7OR0mKTDLLkjN4wM8ThY2nP+7++3d2/D6XwS+9QZP2lq/HUVnqfJwv0HFZV2Qu8BbzFywea07oHLXYZn2QZZmfJzyGLj+fZ2cvQqmqvIWDC4uMbDieTMt6HtTxKF3SZWGRkTWxSfQM8b0xUJFlWPAwnF4PsgnUTubpxB2fg1IuLndDO4ZCRqwcwamMUzirnYuTOXvX782jYY/i6+SLt6M3Dsr/grBsfTbfH/yeRScWsX/U/hseu/b4oSuH6BrQlYLoFFT+MqbMdLSh1l+aIFefy8K4hcyJnUOOPodg92A+6vQRzXyaWb3t8shcsRuFgxqX7i1EQTKhXKxWZGzJkiU88MADKJX/vTCNRiOSJKFQKNDpdDc8BpCXl4eLiwurV6+mb9++Fu18VZBnMLI+PZt7fTxsWgispgQfACtSMunr7Y5qTl9I2ANPbYXazW3ah5Xff8nx7ZsZ9uEX1G1qvzV37uTUlRzi0/LpGeKLsozF8GRZZu2xK0TUdafuzUGLQWee1rz1S9Blm8vK3/udOQgso7NZZxmxYgRGk5HBDQdzKPkQpzNP37CNq8YVb603TmonTqSfwCibL29qlVo2PLwBN40bskmm6HIexhw9OzJ308mzPWofJwqPH8D5nnuQ1BVPaC2ttII0Ptv3GavOrUKlUPG/tv9jWNNhNi8MWBqFZy9RcOAUssGIspYbrt1biEXqhFKz2touvXr1IibmxmuDTzzxBCEhIbz++uu3BB4A0dHRANSuXbssTVUbziol3TxdWZqcyb2+HjYfAakJel4t8NbHPdAcfGRfsnnwERgRyfHtm0mIPVLpgg+TSWbTiWTqejrSO8yvXPuQJIm+4f7sPJNKdkERobWv+2BROUCnF8xr2Gz+xDwlePE4eDmuzDkgwe7B/PvAv6gVatwd3DGYDCw7s4wjKUdIK0gjtSCVtMI0LuVeQm/SE+QWREvflqw4/S9Buf58Ov9dJrSYgI+zL2p/Z5S1HTFdUOEYdHVmkMFg08ADwNvRm8+7fk5UvSje3fkun+z5hOjkaEaEjiDMKwy10rb9uRNtcB20weZpyfpLKWT+sx1M4NqrBWofD/t2TqhWyhR8uLq6EhFx47oWzs7OeHt7ExERwZkzZ1iwYAEDBgzA29ubI0eO8NJLL9G1a9cSp+TWFB5qFX1qubMkOZP7q0kAUplmuzgqFXirVSRHjsb36F+wbxY07W/TPtS7Lu+j/ZBHbNr2nVzJLmRffDo9mvri7FDxb7AdG9Yi9lIWu8+m0T7Y+8YHXXxg0DdXa5LMMU8Zbj6szG1cv5icSqFiSOMhDGl8Y/KwSW8g53waGqMaJPhfref5OnEqfyYsZvuJg3zX8ztauLVgw4UNdKrbqTy/qsX1CepDY8/GvLTpJVaeW8nKcyvRKrV0rNORqPpR9K7fu1IVKtPU8cHr4e4Yiwwc/30rhel51GrTkKCOlpmmLNRsFs3I02g0rF+/nj59+hASEsIrr7zC0KFDWb58uSWbqZKclAr61nJjbaqNZvNcu5pWDQKd0mjt7swu90hknxBzDkJGvE3bd/f1x83Hl0snjmMosk2V27vZczaN+NQ8BkXWsUjgcU14HfOll7WxSSUncLa9WhJ9/2yLtSkbTBSeyaTgRDoFJ9LRJ+TiGuiNY4gXjk29cGlai3d6vMfzLZ8nQ5fB2DVjWXl2JY09GnM597J5HyaTzZKQb6eBewMWDFzAO+3fYVDwINw0bmxM2Mib29+k91+9mXJgCom5iXbt4zUmk8yuM2msP5mK332daPP8YHSZeeyfspQrcQn27p5QxYmF5WzsdH4h2QYjrdwsU2fgdnYvXsSOP+Yx+OVJNGln+W9+lSnn45oUfRE5O6YTvOUd83onUe/btP3VP0whdst6Hn5vMoFh9ksqzNMZ2HQimbZBXvi5We+bdHZhEZvikukX4Y/DzQmKM3vDxb3w9A7wv8MqwKVUeCIdTQN3FJq7J0Kujl/N29vfRmfUMTpsNA80eoDGno3RnTmD5OCAJiCgwv2xFJNsIjY1lmVnlrH0zFIKDOap8ZG1IhnSeAiDGw5Go7Rt6XyD0cSus2kU6I20a+CNu9ONl4WMRiOxi7ZSlJ5HyOjuONtoNW+h8hMLy1VijZy0SEgcz7VO/Y2azEej5mLTIchqJzg415wIaUOB4eaAw+JTbssgLimb3WfTGBBR26qBB4CbVs2AZrVZE3uFjLybppG2GWP+uX+WRdqSZUoVeAD0C+rHrL6z8NJ6MffYXGbEzEBv1FN08SLqunUt0h9LUUgKmvk04632b7H+ofW83vZ1mtVqxpHUI7y/6336Lu7LrJhZ5OitXzVZZzCyKS6ZzSdSaF3fkz7h/rcEHgBKpZLIkT1oNrY3cfO2cHzpLqv3Tah+RPBhBy3dnMg2GDmdb7sqqDVF59p1SWh0L+SnmquC2tB/9T5sX7DJaJJZG5uEUpLoFeqHooyzWcpLrVQwOLI2hxIyiE+9rs5H+APmFXyP/GFe98XGmvs0Z06/OdR2rs2qc6sYv3Y8uUV5lXKGyTVuGjdGhY1iwcAFLLt/GUMbDyVLl8WUg1MY+PdA/jn1j1XqlOTrDaw/doWdZ9Lo2MibqDA/nDR3v0yncXKg9cSBaNyd2T9lKYW5ty8mKQg3E8GHnbTzcCFJV8T5Aut8O7d2BdLKlHB6PYUkIbW99q3bcjkHpeFWywcP/9pcPhVHkc52geWlzAJWH02iS2MfGvtZr5z87UiSRM8QP1JzdRy5mGm+U62FFiNBn2sOQCrAkKVD6V72Amsn0k/wx6A/6FinIweTD/L5vs85m1X5114Bc27I+x3fZ83QNTwe/ji5Rbm8u/Ndnt/0vMUqpmYVFLE2NokD5zPo3tSHHk19b718VgoNu0cSMa43R2eu48xm+436CVWLCD7sqLOnK2fzrXtpoLIGCdYUGNyOTN/mcH4HJNu2amNgeCRGg4FLJ+Js0t7OM6lcyixgYGRtHEt5WcJa2gR54ahWsu1UytU7rgsCK/CN3ZCUh9qv7EXLcvQ5aJQapvWaxrAGQ7mkT2HUylHsubyn3H2xNR8nH15p8wp/3fsX4d7hbE7YzJBlQ9icsLnc+0zN1bEmNoljl7KJCvWjS2MfVMqKnQq0Lk60efE+dOm5HJ67sUL7EmoGEXwI1ZJTu/Hmf9h49KP40ssx634DzCksYvnhSzT2daXNtRoWlUBjP1ea+LmyMuYyJs9gqNMSrhyFzAvl3qcsg1SOy0hDGg8hOiWabRe3McKhC/f2e4FcfS5Pr3uaf079U+7+2EOwezBzB8zlqcinyNRl8tzG5/hg1wdlKtl+KbOANbFJnE/Lo0+YHx0aelv88lzYkI64N/TnwNQVGMu6yrNQo4jgQyiXyraw3M00zYZicHDHdHgh6MqwPHwFefj6A3ClIivc3kXspSz2x2cwKLI2Pq6WW+/FUvzctHRv6sOmbVuRLx8G90Bw9bd5P1QKFR3rdKRHvR6kZiXi59+Qb7p/g1qp5t2d7/LNgW8wybZbe6mi1Ao1E1tO5Lf+vxHoGshfJ//i6fVPk62/8/T9c6l5rIlNIi1XT99wf1rX97Jq7ktQxzCC77+Hg18tJddWpQWEKkcEH0L1pHFC1XIkCl0O8lHbrPNSpNexbuY0ABq2bmeVNk5dyUFCokeIb6VOnnTSqOiZ+AOSbCKrwxvlXhTPkFmIyqPiAVaoQ326BHRBRubTzp/i6+TL7KOzeXXLq8XTW6uK5j7N+X3Q77Tzb8e+pH08ve7p4nVwrnciKYc1sUnoDSb6hvvTLMC9hL1Zh2eADy1fvJe4uZu4sPeEzdoVqg4RfFRX1wYmrHR+qhK5JK2fACBvz4wK5RyU1uZfZpASf5Ym7TrRvLd1KqwmZhYQVqcK1L+J34F0cjX4N+OwZ29OXSnfjJeiK/mofMue73ELSUKj1BBVP4raLrWZ2GIiDd0bsu78OsasHkNKfkrF27AhV40r06Om0z2gOzGpMbyw8QUMJgMAMRezWBubhEaloG+4P039bZ+EDKDSqGjz0n2kx17g9IbDdumDUHmJFYOEcnl98RGSk7Nx0iiRoPhbuPnf17aSiv99/f3S1fsHNKvNO4OsWKrZpwkEdcElfht5F/bhXP8eqzV1bNsmjmxYjYd/bfo8/bzVRiUq98Wu6+z8zvzT0YuujvEc1jXhwPl0WtcvY35KOfM9rmfMzER5XcGjUO9QQr1DUSvUrDm/hs0JmxmxcgTTek2jiWeTCrVlS2qlmi+7f8nT655mT9IePtj2HV1qjSCirrtNRznupsUTvYlZuIW4FXsJGWi996BQtYjgQyiXy1mFTBvWgkAvpxsGFWT5v3wQ87+v3S9f92/YcPwKMYlZ1u9o27EQv420XT9bLfhIu3iBdTOmolSrGfzSJBycrFu9tkpo2h8u7IZzW+DcFpp7NSSjyUPsSO1Px1bNbXrJqDAuDseWLW+5P8QrBBeNCwoUbEzYyKOrHuWLrl/QJaCLzfpWUWpJw8P1J3E8bQzL4n/l/pBu1PGwfX7N3TQb3o1jS3ZxfNluQu9tb+/uCJWAuOwilItCgrDa7oTXcSei7n+3ZgHuRAZ4EBngQfNAD1pcvbWs50mrq7fW9T2p52WBofTSaDoQnH0JOL2c46mXLb77osJCln/zKQadjp5PPIVvULDF27gmLVeHt7NtS22XW+vH4dWT8PBv0KQfZMTjuftTOi7vTuoP/TFGLwL9nYtSGdILUXlWPN9D1utRONy6n0aejege2J2vu3/NiJARFBQV8OyGZ1kYt7DCbVqbwWhi26kUNsQl0zGoAZ93+wQTJt7Y9gaxabH27l6Jwu7vgKGwiLgVe+3dFaESEMFHNWWLJXsq8uVVBhIzCqzfT5UGWj2KwlCIKXoBBpPl2pNlmfUzp5F28QKhXXrQrGdfi+27JMcv5xDiXwXyPa5ROUDYfTDid3j5OPT5GMk3FJ+UXSiXPIX8ZWNYOhHO7yoxJ6coxUL5HnehVCj5X9v/MT5yPA5KBz7Z8wnPbXyOTRc2sSNxB9sTtxf/3Jm4k/wi+1Xy1BmMbDqRzJaT5hLovcP8cHdU0zWgK4+GPUpSXhLD/h3GOzveIUtng5HFMmr2cBdkWeboH9vs3RXBzkTwUd1V0hkRdTwcOZuax7ZTqdZvrPXjICkIPb6QjWmW+0BOjIvl2LZNIEmEde1p9UsJRSYTGlUVfcu6+kHHiTBhJzy5BfmeJylCBYfmwpx+8F1L2PL5jfVAZCp8TEsb3CoVSia2nMiiQYuo61KXzQmb+euUubBX57qd6VS3E53rduae2vew+/JukvOTK9SvsrqhBHpDb3qF3loC/dU2r/J196+p51qPJaeXcO+Se9l0YZNN+1kaoYPaoXTScOzvnfbuimBHVfSTTLA3CTBVYNSiWxMfIuq6UVBkg0JEHoHQuC+KtFMEJe3hYmHpCzPdiWftuvg2aAiyzOKP3+HP/3uThNgjNhl1qrIkCeq0QBrwBZr/neJEt+nk1O8NWQmw6WOY0gx+GYQcvQAMFR9hKEpMRF2GVWwbejRk/oD5RPpEsvXiVsauHUtSXlLx4yqFip71enI09WiF+1YaZSmBLkkSvev3ZvG9ixkbMZYsXRbPb3qeMWvG8PX+r9mZuBOd0baLLd5O6CDzVPQTK/fZuSeCvYjgQygXGfM6KhWhkCTbnaivlvpucnw+B7LzLNKus4cnoyZP4f7/vYt/oyZcOHqEPz58k9/ff5346AMW/d2KjCZUNloszmZUGpr2GEFC39nsG7IT+k4Gv2YQvw1pyQS0S++BJc9A/HYwla8YmP7cOTRBQWV6jrejN7P6zKJfUD9OZpxk+IrhxKbemEfhonax6uhHSo65BPrxy2Uvga5VaXmx9YvM7jubui512Ze0jzmxc3hq/VN0XtiZCesn8MeJP0gtsMGo4x2EDelIQXIWFw+csms/BPsQs10Eu5GwSfkNs0a9wKMexK2gc9TH7MxU0cmz4vUPJEmiYet7CG7VlvNHDrH770Ukxh1j8eT38G/UhPZDHiG41T0VvnwQV9XyPcogrI4bFx1VrE4cQt+nJyAlxWDYPAdlwlKInm++edSDNmOh4/OgKMN3JllGKsv2V2lVWj7r+hn19Tp+urSJx1eO4tPAAfRyDwGFinsUSvbFbyXOZKJ9nXZoGnQrcxslScwsIDYxC28XB/qE+VXoddPKrxWrhqwipSCFwymH2ZG4gx2XzLkr2xO388meT4iqH8XosNE092lukf6XVYvHo9g/ZSmudbxxr115lgkQrE8EH9WW+axurWJgFokZJMl2dSsUSnPRsQ0f4B2zCF3EU+QYjLiWYxXPkkiSRFDzVgQ1b0XCsRh2L17IhaNHWPL5/+ETFEz7IY/QuG2Hcp0IAVLzdJWqdoOlBXg64eaoZtnhS/SLCMfU8h1UD30Gp9bAsufNuSDr34fmw835IzagkBRM3LeY+nUa8y5pvHRhGS+xjcdlVySTkbYmI3pTEXt2/4DJvQ6N67Sndp22SH7hUKuJeWXfUjqXmsepKznU8XCkT7jlpspKkoSvky+96/emd/3eyLLMyYyTbLywkaVnlrImfg1r4tfQqW4nXm39Ko08G1ms7dJq+dwgDn61hBYv3IvaQW3z9gX7EMGHUG4Vza+06cgHQMvRsOkTOPAL3Tu/xIq0HAb7eli8mcCwZgSGNSPxxHH2/L2Ic9EHWP71ZLwD6tFuyCM07dAZhcK+K9BWRm5aNQOb1WZVzGXao8YxPw32zYSCdHBwh8FTyhR4yEVFoKzgcZZNDB74M7WN2by4+UW+1mVwvklP3mr/FmqFGg3QJT8d44mVnD+/lR0Hf0LOPA+GQhz9m9Os0UAc6ncE/0hQ3npiPZGUw/m0PIJqOVs06LgdSZJo6tWUpl5NeTLySTYlbGJGzAx2JO5g16VdPBb+GBNbTESjtN2UbqVSSdiTfYmetoK2L99vs3YF+xI5H0K5WCJokKSKJa2WmYsPhN0L2RdRnFpLqIuW2FzrretRt2koQyZ9wMhPvqFhm/akXbzAyu++4JeXnyF2ywaMBoPV2q6qVEoF/ep6knJhNcYfOsDZzVCvA0zYDhFDyrQv3alTODRuXLEOySaQJNr4t2HBgAUEuQWx+NRiJqyb8N9UVicvlC1HEXz/z3Qes5kuL52ly/jdNKnXlegzq9j2x0Ps+LENRXtnQo45efXIxUzWxibhoFLQJ9yfJn62L4GuVCiJqh/FwoEL+aTzJ3hrvZlzdA4jVozgTKb1FkYsibOHC7V7RHD41w02bVewHxF8COVW0TwGCTuUC28z1vxz/2waOWk5X6CzaO2Pkvg3bMz9r73No59/T5P2nclIusTqH75hzktPcWTDaoyGojs+Pzm7EB+Xyrd6rVXo85HWvErYwedQ6LK53OoVeHyFOeejjAypqah9fUu38ck18Ou9V2+D/7sZCkEyf0zWc6vHvAHzaOvflj1Jexi9ajQJ2Qm37kuSwLM+bt3fpN3olXR54RQtWj3JvqPz2PhjG9b92AO/S6vpE+5PUC37V8NVSAoGNxzM3/f+Te/6vTmRcYIRK0aw9eJWm/YjoGUjJKWCi4dO27RdwT5E8FFNVYXZnjad7XJN/Y7gEwKn10NGPD293NiYbptlv33qN2DwS2/w+Jc/ENq5O9kpKaz7eSoznx/PodXLMehLngIcl5RDiJ0WB7OppBj4uTuq0/OR3eohjVlNXvuX2Ho63fptX9htHuWIfAQih5lvzYfDg7PBs0HxZu4O7vwU9RP3N7qfc1nnGLlyJIeSD91x1yYUHPZ9hNx2i2g5bB1dmj1A9M63SVnxEujKt+CeNXhoPfiq21e83e5tdEYdz218jvnH59v0PRo5qgeXNx3FaLTBFHzBrkTwUd1V0iJjYKeuSdLVabcy7J+DVqmgllplsdofpeEdEMiA517liW+mE9GjN/mZGWyc8xMznxvL/n//oaiw8IbtTbJc6mmWVZLJBLumwYyekHoCIodheHg9BdnBBClVhPi7suLIZUxWHqGiVhNoOfK/W4sREDH0ltk1aqWaDzt+yAutXiBDl8HYNWNZcXbFLbu7VgJ9Y1wyEXXd6RPuj2dgKNpOz9N35EouXN7PsT+GW/d3KiNJkngk5BF+iPoBZ5Uzn+79lHd3vmvT+iBBg+/h6PzNNmtPsI9q/IkmWFtFYwcJybY5H9c0HwZqJ3N1TYOOVu7OHMzOt/kojGftuvR9+gXGTPmZ5r37U5ibw5a5s5gxcQx7lvyJvsBcZKsKDGKVX84VmP8grHkTlA4wZAYM+Ql1gB+O4bUw6Yy4JuTSrbY7yw5fIl9fujwZY24eCifrlWaXJIlxzcbxVbevUEgK3tj2BtOjpyPLsrkEepy5BHqb+l5Ehfnhpr0p2dSnCS3veZ7Llw9YrY8V0bFOR+YNnEeQWxBLTi/hmfXPkFeUZ5O2fRrXwZCvIzfVNiOSgn2I4EOwG0kqd+2oitG6Q7MHIT8Nji8HoKOHC7sybfPhejN3Xz+ixj3L2O9m0rL/YIoKC9m+8FdmPDuG7X8sQKG3XlKsTRVmw8X9cHAurHkL5g2FaW3hzAYIuMecVBr58A1P0dRxwTG8FppCI71VGrZHX+ZKduFtGviPLu442tDQMnSufCFen6A+zOk7B2+tNz8c/oEnVrzI1lOX6dSoFr1C/XDU3H62jUGhxIDM+aVPlattawt2D2bBwAW082/H3qS9PLnuSZutaxP5RG/iFmyxSVuCfYjgQyizayMEFb1sorBlnY+bXa14yr5ZANTSqNCZTOQY7Het2dW7Fj0ff4pxU2fRZvAQjAYDexYv4PBXr7F90W/kZ99hXRpdLmRbftXecinMgoR9cPA3c5Axdwh8HQ6fBsLMXrBsIuyaas67MZmg2xvwxCrwDLrtLjWBrjhF1KKbnzsX91zi5PmMO3bBlJ+Pwtk2yZz1nEN4uvG31HFqwIG0jcyNf5NcQ+Zdn6eJGELfEf9y8sRSSDlh/Y6Wg6vGlWlR0+hStwtHUo7w/MbnydXnWr1dtYMax7peovppNSbqfFRblgkQrEmhsPFU2+vVaQl1WsGFnXDlGPiF0d3LlX9TsqxS+6MsnD086TZqDG3vHcrfcxeQsW8je/75g4Mrl9G8zwDaDHoAZw/P/56QkwSz+0JGPLjVhYA25pGEwHvM9SXKUOyqTAqzzCfNlDhIjjP/TImD7MRbt9W4Qt025mRf3xDzT58QcA8o9YtUkiQc6rvRqp4rx/cmEnM2i/AOASi09vkYS8nRcehCBu6Oah5pGcmgiAW8uvVVdiTuYOSKkUyLmkawe/Cdd+IXbr58mW+DpNpyclA68FX3r5i4YSJ7kvYwZs0YZvWdhavGuknQ4UM7sX/KUgJaV3C6tFApieBDKDNLxQsmE/yxLwG9wXzt5do56PqqrP/dZ/63hMTV/5Akqfh+hST9t+1190tIV39eXdPMw5HIAA/zhm3HwtKDsH82DPwSSZIIc9FyNCefCFfrL+V+N05u7tSNGsqDj43m0OrlHFy5lP3L/yZ69b80i+pL23uH4uqoNI8sZMSDT6i5EuixpeYbgFJjDkAC2kJgW3NQUoYTPgAFmf8FGdduyXGQc+nWbTWu5rZ8mpr7cy3YcKtrsUhYkiTC2gUQn5LLnp0JNPd3RdvIE8UdLnEUy0s1j7jIJvMLWTaZbwd+BdfapWo/MbOAY5ey8XbR0Pu6EuguGhem9pzKZ3s/Y9GJRYxaMYqve3xN+9rtb78ztSMRIUM5tOoFWo5eCc61StUHW3NUOTI9ajpvbHuDdefX8dzG5/gx6ke0KisFtld5tmjAidX7adqvjVXbEWxPBB9CuVW0dHv/Zv6sP57MhuNXii+/XB/Y/HefXPyYjGz+ef2/r258/f/Lsnz157XHZc6lmnM6jrzf17zj8CHmRMfDiyDqfXBwoaGTlhUpmYQ4O1aahdy0Li50eHA4rQbcR/TaFRz49x8OrVrOsfX/MirsPB7689DsIXjgZ/OJNOU4JOyFi/vMt8T95tue6eYduvj/F4gEtIU6LUDteF2Qcdz8M/m4OdDIKeFyjoOb+fk+TcE39L9gw62OzYbbgnxccG+nYf3JFHqezUShN+EU6UPRlWRUPj4lPynmT1j9BgR1uRqdKsy3gvS7nvivL4HeO6zkSqsqhYq32r9FkHsQn+/7nAnrJvB2+7cZ2mTobffr3/sj0haPZuOPrYkIfwTfnu+Bxv71P26mUWr4tMun5Ohz2H15N69tfY1vun+DSmG900jD7pHs/3YZ9LNaE4KdiOBDsJtHOwTxaIcgm7V38EIGz8w7+N8dGidoPsJ8Uj76F7R+HIBeXm5sSM+mby37rqVyKbOA2u7/fbN0cHKi3f0P0arfYI6sXU6tnW/ioU/mXJ4Xp5JDaZuchKd/HfBvZr61vVpQLT/dnOh5ca85KEk8aE60vZpsi0IFjl6QV8IqrQ7u5iDj+kslPiE2DTLuxNNZQ99m/qyNvkRHrRYnzJVNndu3K/kJsgwhg2DY/FK3EZeUzYW0fBqUoQT6yNCRBLgE8NrW13h/1/uczznPi61eRCGVkGbn6En4qH8Jv3iAQ2te4djMjrQOH4Zr81HgEVjqftqCRqnh2x7fMnbNWDYnbOb9ne/zf53+r8IFB++kVttGYvSjGhLBR3VlxVyKa3uuBOeeimszxhx87JsFrR4DSUKrVOCjVpFQqCdQa7s1Lm52KjmXzo1u/Tau1mhoXbQWtMnkujRmY3IImZs3cXTLFkI6daXdA4/gHXDdScvJC5r0Md8ATEbziEbC3v+CkrwUCGz3X3BxLdhwrV3p/9AOKiW9HB3ZbioiND0fT5MRSXWbj7aSTv63ceRiJklZhTT1dy3XuivdArsxt/9cnt3wLHOOziEhO4FPunyCo8qx5CcEtKbl4+swHF3M4Zh5ZO6fjqNPKMF+zfHv9RGo7PdavJ6T2okfon7gsdWPsfTMUhp7Nuax8Mes1l5QxzAOfP+vGP2oZkTwUe1V7hPHnUyfPp3p06cTHx8PQHh4OO+++y79+/e3XCM+TcxD8PHbIPGAOVkTaOXuzNLkDAIc1Fb9VncnJllGefOlH1mGNZMg5g/wDcPl8RU8pnbl2NYN7F3yJ8e3b+b4ji00adeJ9kMewad+g1t3rFCCX7j51uYJ2/wyVmTM1aN0VtMnqBa7z6aRlZpHxO02lhTmS1O3IcsyB85nkJFfRERdt//yg8qpqVdTFgxcwHMbn2P9hfVcXn2Z73t+j4/TbS4LKdWomg+jdfNhkHwc47mtbD/4M875mbhG/Z/NVvS9G0+tJz/0+oGHlz/MlINTaOvfljDvMKu1p3J3JP1CMl71SlkuX6j0KjTV9tNPP0WSJF588cVbHpNlmf79+yNJEkuWLKlIM0IlY6tiXAEBAXz66accOHCA/fv307NnT+677z5iY2Mt29C1abf7Z99wdycPV3ZmWn9aYZls/RL2/Ghe62TU3+DkhUqtJrJXP5745if6PfMSnv61Obl7O7/97zmWfPERV85W77Uy9Oez0dR3A6BdkCcKhYKdZ1Lv8Ixbg0mTSWbnmVTWH0+mQS1neof5Udv9NiMUZeTr5MucvnPoGdiT2LRYhq8Yzon0Ukyt9Q1F2e4pOvb9huiUw6ybcQ+62H8s0idLCHAN4N2O72IwGfhg1weY7hDUVVT4sG6cW77XavsXbK/cwce+ffv46aefiIyMLPHxKVOm2O0bo2Ab1v7rDh48mAEDBtC4cWOaNGnCxx9/jIuLC7t377ZsQyGDwNkXji6+YcqjufaHTLYdan8UFhlxUN309tw3EzZ9BM4+MHoJuN04O0OpUhHerRePfz2dAc+/hndAPc7s3828SS/y9+T3uHTyuO1+ARsxpBei9NQWf9boz52jUZsI6ns7s/poEnk6A9tPpbL5RDKbTyRzMTOfwuv+ngajia0n/yuB3jvMD+8KLOI3bdo0goKC0Gq1tGvXjr17zSdMJ7UT3/T4hifCn+BK/hUeXfVoqRduUwd3pcuTe+jR5ys2rn6RU3+OgjTbrjp7O/2C+tGlbheOpR1j2ZllVmtHpVEhVZIEcMEyyhV85ObmMnLkSGbMmIGnp+ctj0dHR/PVV18xe/bsEp4t2EJVWFiuLIxGI4sWLSIvL48OHTpYducqDbR61LyC6eGFNzzUw8uVLem2X/wr9lIW4XWuS3g9+jeseNU8y2TUYvBueNvnKhRKQjt147EvpjL45Un4BAVzLvoAC995jT//700SjsXY4DewjaLLuWjquPz3/4mJqOvWoa6HI50aeXM4IZM2QZ50b+pL18Y+eDlp0BtMrD56mbWxSWw7lUrboNuUQC+j33//nZdffpn33nuPgwcP0rx5c/r27UtysjmRVyEpeLnNy7zX4T30Rn3xwm2lpYp4kP6j1+CgcmDtLz3I2fyxeYq1wXbrEpXk1bavopJUfHvwW6uWYNd4u5FyqoTp3UKVVK7g49lnn2XgwIFERUXd8lh+fj4jRoxg2rRp+PuXPUlLsCxrjD4VxzU2+CISExODi4sLDg4OPP300/zzzz+EhVnh2nLrx835APtn3xC5XV/7w5ayCw24O149GZ7eAH8/aa7ZMXwh1G5eqn1ICgVN2nVi9Kffcv//3sW/URMuHD3CHx9MYtF7rxN/+KDtVxW2IP3lPNT+t05Jvfaad9Wq6dioFlq1uf6HQiHhpFHhplXTL6I2vcP86BHie8cS6GXx9ddfM378eJ544gnCwsL48ccfcXJyuuVL2INNHmR67+nFC7d9sucTDKbSrVmDbwj1HphF74f+JObkcnb83IHtXzdgx3eh7JjVhbwtn5lH8PLSLPI7lUawezDDQoaRWpDKzJiZVmun6X3tSdh42Gr7F2yrzMHHokWLOHjwIJMnTy7x8ZdeeomOHTty3333lWp/Op2O7OzsG26CcE3Tpk2Jjo5mz549TJgwgccee4xjx45ZviGPQGjcB9JOmxc6S44rfqihk5bzhXoM1l5VtSQX98Pvo81Jkg/9AkGdy7wLSZJo2PoeRnz0FUPf/JC6IWEkxsWy+JN3Wfj2q5w5sLfKBSGyLGNMK0DlXf68DEsG5nq9ngMHDtzwhUyhUBAVFcWuXbtu2b597fbMGzCPui51WRi3kOc2PlemsuVSvXZ0fHI3nV5LpPO47XR64DfuaTmOuIs72Lbzc9ZPb0HhTaN41vR086fxcPDgt9jfuJhz0SptqB3UyPZ4DwpWUabgIyEhgRdeeIH58+ej1d5a2W7ZsmVs3LiRKVOmlHqfkydPxt3dvfgWGFi55rULt7LleUqj0dCoUSNat27N5MmTad68Od9++611Guv7CdRuYa6AOb0jrHil+BvktdoftlAcCCTHmQOhojy493sIGVCh/UqSRFDzVjzy/mc8/O4n1IuI5PLpEyz5/EPmvfEip/bsRLbLSn9lpz+fjSbI7Yb7TIWFSJq7TUe1zos3NTUVo9GIn9+Ns1H8/PxISkoq8TnBHuaF21r4tGB74nYeXf0ol3PLuD6PQgFeDSCwLepWj9F65DJzfsign1i/YRLG6IU2Wb3R3cGdZ1s8i96kt+roh8j7qD7KFHwcOHCA5ORkWrVqhUqlQqVSsWXLFr777jtUKhXr1q3jzJkzeHh4FD8OMHToULp3717iPidNmkRWVlbxLSEhocK/lGAbFa1wWh4mkwmdTmednXs3hPGb4P4fwcXXnOD5XUvY+T1a2VBc+8PaLmYU0ECVBnMfgIIM6PMRtBxpsf1LkkRgeCQPvfMJwz78gqAWrUmOP8Oyrz/h19cmErdjCyaT/RbYuxvZJGPKN6B0uTHQ0MXFoQ0JufsOKlEivJfWi5l9Z9K/QX9OZZxi+IrhHE09WuH9KkMGENXnS7Zu+z9OzL8XDFZ6z1xnSOMheGm9WHluJdl66wTqDt6upJ6uJAsoChVSpuCjV69exMTEEB0dXXxr06YNI0eOJDo6mrfeeosjR47c8DjAN998w5w5c0rcp4ODA25ubjfcBEuo+sOTkyZNYuvWrcTHxxMTE8OkSZPYvHkzI0da7kR8C4UCWgyH5w6YV1s16mHt2zDtHlpd2sShrDyrX6K4kHCe+itHmddO6fQidHzOam3VbRrK0EkfMPLjr2nYph1pFy+w4rsv+OXlZ4jdsgGTsfIFIbrTmTg08rjlfmN2NkqPW++3hVq1aqFUKrly5coN91+5cuWuuW8OSgc+6/IZE5pPIK0wjSdWP8G68+sq3CdtxIP0GL+L7II0Epc9A8ZS5pWUk0apYUjjIRQYClgTv8YqbdTrGk7iruo3a6smKlPw4erqSkRExA03Z2dnvL29iYiIwN/f/5bHAerVq0eDBiUUOxKszwpf8mQbrZibnJzMo48+StOmTenVqxf79u1jzZo19O7d27oNg3ltjR6TzEFI5DDIOAe/j6TfilEcPrXHeu3qcmi2ZRxS2mloOdq85owN+Ddqwv2vvcPoz76jSbtOZCRdYvUP3zD7xSc5smE1RkORTfpxN3KRCVmWS7eInA1pNBpat27Nhg0biu8zmUxs2LChVLOzJEnimRbPMLnLZIyykZc3v8ysmFkVD3S17rR9aCFnLu8nccl4KLTupcM+9c1VdLcmlG4acVm5+npiyCu0yr4F26pQkTFBsKZZs2YRHx+PTqcjOTmZ9evX2ybwuJ57XRjyE4zfCIHt0VzYTvMF/dD/84x5KXtLKiqERSNwSz9qrj0yaIrNLxH4BgUz+OVJPP7lNEI7dyc7JYV1P09l1vNPcmjNvxj09p3WWXg6A22jW6f3VwYvv/wyM2bM4Ndff+X48eNMmDCBvLw8nnii9FVkBwUPYmafmXg4eDDl4BTe2/keRcYKBn6eQXQdsZSUzLPELhpq1aStEK8QfB192ZO0p/QzeIQaqcLl1Tdv3nzHx6taFr1wd1X1T5qeqycpu5CPV5hny5Tt93AE368JUW+k18VpeB6ejz7mb3b4P8pu/2EYFCUvLe7lrOGZ7g3vPrPCZIS/x8G5rWT5d8B96CxQ2m/1A++Aegx47lU6PDicPUv+5Pi2TWyc/SN7/vmDtoOHEBnVD7WDdZdTv5kpbhuKQzuQzqZiXsZYLv5pyNOhTM2HzD+v+8Nev+Tx1W1TTpgXxbOCRx55hJSUFN59912SkpJo0aIFq1evviUJ9W5a+bViwYAFPLPhGf45/Q+JuYl83f1r3B0qsNChZxAtRixh76yunJh/L00fWggOLnd/XhlJkkQzn2ZsuLCBCzkXCHYPtkobQtUnRj6qKVsEfVXtI6Cxn/nDNl9vpMgoYzDJGOUy3IBYz578EL6Qf2s/jQmJHpd+YsLR4YSlrUU2ychXz3OyDCk5Or5Yc4Ii413+FrIM/74Ix5eT5x2BcsQCUNv2xH47nrXr0m/Ci4yZ8jORUf0oyM5m828zmTFxLHuX/oW+wHb1T3R7dqHJXWdejVjjAlo30HqAkxe6dAUOjYPBxd8cXLjVBfdAcxl6zyDzjBCvhuYZQx2etVofJ06cyPnz59HpdOzZs4d27W6zuu5dBLoFMm/APNr5t2Nv0l5GrRzFhewLFeucoyf3jN1GZkE6mTu/qdi+7qCxZ2MATmdU77L+QsWIheWqOXvMSKms6ns7E//pQAvtrSXrz4+j5+GpeBz6jaHn3mNo0b/QdzIEtgUgOaeQZYcv3f3KyYYP4eBv4N2IQ11n0tnNy0J9tBx3Xz96j59I+yHD2LdsMTEb1rBtwS/sW/oXrQbcR8v+g9E6W/6b9DWGzEKUDgVIAd2g17u3PC6rt6Lo2tVq7duDu4M703tP56PdH/H3qb8ZuXIk3/b4llZ+rcq/U0cP7un5MRuXjaVXh+dBW4HRlNvwdzIn2KYVWqfQmRj5qB7EyIdQbjX9Q6BzQEPWd/wQnt4Owd3h4j6YFQV/jYXMUk4Z3/k9bP8aXOvA6H8o0npbtc8V5epdi55PPMW4qbNoM3gIBkMRO/+cz4xnx7B90VwKcqyT0FiUmIvGJdMq+67M1Ao173d4n5dav0SmLpNxa8ex/MzyCu1TCu6Gl3t9kjd8YKFe3shFYw5Cy1I0Tah5RPAhCOWkVSqopVaR4N7YvNDb8N/BuzEc/QumtsF5+2ScuENmfvQC8zReR08Y/Q+ye9UpsOfs4Um3UWMYP3U27R54GJDZ88/vzHh2DFvmzSYvM8NibRVdyUPl63Tbx6t7XpkkSYyJGMM33b9BKSl5c/ubTIueVv7fW5Jo0fYZjpxZadmOXuWgNC/MV2i0zqyU6v73rilE8CGUmXjv/6eVuzMHs/PMeY1N+8Ezu6DfZ6DS4rxnCpsdXkaKnn9rlcm4lbB0IqidYMSf4BtCfFo+Qd63rlVSmTm5udN52KOMnzqHDg+OQKFSsn/538x8bhybfvmZnPQ7LW1fOobUAtQ+tw8+ii5eRB0QUOF2Kruo+lHM6TeHWo61+PHwj7y+7XV0xvIVDzt56l8iGva3cA/N9EbzjKhrQYilieCjehDBR3UlEk5tppOHKzsyrw4xK9XQ/ml4/hD5rcbjSQ6q5RPh524Qv928TfwO+PNx80J2j8wtzhGJT8sjyPv2J9nKTOviQseHRjB+6hw6D3sUtYMDB1ctY9Zz41g/cxrZKcnl2q/uQjaaQNc7bqOPj0cTFFSu/Vc1EbUiWDBgAY09G7Pq3CrGrRlHemF62XaSl8aFC9vwa1Kxcv23ozdZN/jQeLmSds7C09wFmxPBR3VXw/MybKGWRkWRSSbbcF01UCcvcnt8RF/9Z5ga94OkI/DLQFjwCCwcZq6cOuQnaHTjytBVPY/GwcmJdg88zPips+k2agwOzi4cXreKWS+MZ82P35KRVPol0WWTjClHj9LtLicxWUZS1JyPstoutZnbfy6d63YmOiWaEStGcDbzbOl3kHoSR0mN1Ng6NXOUkrkAXH6RdWZCBUe1IGFLxUvQC/ZVc96xgsXYqsJpVdLdy5XN6Tm33H9WroNx2EJzTohvOJxcDbpsGPglRAy1fUdtRK3V0mbwEMZNnUXPJ57CycOTo5vWMefFp1k59SvSEu+ekKs7m4lDQw/rd7YKclY7833P7xkRMoLE3ERGrRzFrku3rp5boszzmJytN6MqzDsMgKNp1gkQnL1cMdpgjSXBukTwIQgWIEkS4S5ajubc+m1PAmjYA57eBg/8BENnQdtxt2yXp6t+FSHVGgda9hvM2G9n0Hv8RFxr+XB82yZ+eeUZlk/5jJQL8SU+TzaYkA0yCu2dqwHIRUWgrFyl1m1FpVAxqd0kJt0ziTxDHhPWT+Cvk3/d/Yl1WmFIPwc5V+6+bTnUc62Hu4M7R1KOiPwM4bZE8FFNWfMtLz5PStbQScv5Qj1FptscIIUSmg+DZg+W+HDbIC92nbFObQR7U6nVREb1Y8yUn+g74UU8/Wtzctc2fnttIku//IgrZ28sSFV4OhNtCYvH3Ux36hQOjRtbqddVw4jQEXzf83sclA58sOsDvtr/FSbZdPsnSAqUsslqhewkSSKyViSZukwScqyzSnlVvzwpiOCj2rPmW1QUMLtVLy83NqaXr9aFn5sWB7WCC2m2qxpqa0qViojuUTz+9XQGPPcq3gH1OL1vN/Mmvcjfn77PpZPHMRUakFQSkuruH0+G1FTUvr426Hnl1jWgK7/1/w1/Z39+if2Flza9dPucC7c6uHsGc2jeoNLXoymjSJ9IAI6kHrHK/oWqTwQfgmBBWqUCH7WKhHJek25Vz5Njl7MpLKp8S9lbkkKhJLRzdx77YiqDX3oDn/oNOHdoPwvfeY2Nk6eRorvNSVEMu91WU6+mLBiwgAjvCDYmbOSJNU+QnF/CLCONEy2e2IiT2pkL2z61Sl/CvcMBOJF+wir7BzAaq/d7pLoTwYdQZsUf/2Lgo0TXan+U99pX7zA/1h+3zvX4ykZSKGjSvjOjP/uO+//3DvWCm5Fw7ih/fPgmi957nfgjh67LGxAvuLvxcfJhdr/Z9K7fm2NpxxixYkTJAYBSw5Ws8/jXaWuVfvg6mUejUgsqXuelJGpXR3KSLFfITrA9EXwIghV08nBlb1ZeuZ6rVEjcE+TFzjPW+eCujCRJomHrdgwc+Qo9Xn6aOk3DSIyLZfHH77Dw7Vc5e3DfLcmLxtxcFM5VqyibLTiqHPmy25eMiRjDlfwrjF41mi0JW27aSkKrdiL7cvStBfAswNvRvExAmWuQlJLKRYsup8Aq+xZsQywsZ2fWGkRWKMwzAIxGy8+gUEggKQsYMmc2CkXpvo2W+jtrGb7clnbTknNTSv42bcl+5hQZUToXsPOSG8py1KE4k5NL0nEVfm6VY4VbazNk6QAZlY+WwCfvRXs+krgdm9l/Ppr9s6LxcFUT4p5CncQdSBLoknWovTQoYkv+Y9zwFy73G628T7Tx5aESLkfdAxThwvyiXJ7bMJEHcaEnjsXvB1mfy1+nF/N04sjiQneWZq3EUNlgQlFDZzlVFyL4qKYcnMyVMvX5lk9edNKomPPQeHIKSx/YlOdSvVzGD/CytlGe00OZpg7KcKJIT9fABuVoCTrVhdVHk2jt64NWXf0/aAsyU3GMqPXfHQGdodMoEuOOsfvvRcQfPkgCtSm46Ea7DqHU8dDj1rzR3Xdc5hNgGbevxPvvBHTLieel83/zpzEXhXcT3qjbB5VkDoY7K1Tg36yM+787g8n82aBWqC2+bwDZZEKpFqevqkz89ezMWlexHZzMw9G6AusMTXZp7GOV/VY3Z/N1HM3JJ8K1fGXTe4f5sTLmMoOb17FwzyoX/cUc1HVdSnysbkgYQ9/8kMunT7Dnnz84s38PK5bvwcPDi/aNuxPaubv4FnwH7YB5kY8wccNEfk87yEWtI192/bJ49VlryCsyX3J0VDpaZf+mIiMKtcgaqMrEX8/OrDU46+Bs/mApyMmyUgtCaQQ7OXDhTrU/7kKpkGgX7MWO09U3/0OWZYxZOlQed768VLtRU+5/7R1Gf/YdTdp1IjMzndU/fMPsl57iyIY1GA1FNupx1RPsHsz8AfNp6duSHYk7GL1qNJdyS1/qvqwu5lwEoI6LdYLmoux8XP09rbJvwTZE8FFNedc1r/KZej7evh0R6OnlxqZy1v4A8HXV4uKg4lxq+RJYKzv9uSwcGriXenvfoGD6jRzD8GdfJaRTN7KTk1n38/fMeuFJoteswKAXpbdL4qn1ZGafmQwMHsjpzNOMWDGCIynWqcNxNsu81kw9t3pW2T+AUox2VWki+LAza1128aobiErjwKXTJ0SJYzvTKhXU0pS/9gdA80APTl7JoUBfvWobyEYZU6ERhVPZcgN0p05Tu2NnBj7/Go9/PZ3wblHkpqexYfZ0Zj4/jgMrllCkK7RSr6sujVLD5M6TeabFM6QVpjFmzRjWxq+1eDsHrhwAoLlPc4vvW6geRPBhZ5af5GamUCoJDG9GbloqKefPWakVobRauTlzKDu/QoFgVGj1q/+hO52BtnE5hs9NRiSVOWXNq05d+j3zImO//ZnIXv0oyM5m828zmTFxLHuX/oW+oPpWjC0PSZKY0HwCn3X5DJNs4pUtrzAzZqbFvqTojDoOXDmAl9aLYPdgi+zzZuILVdUngg8700gSOivMswdo1KY9ACd2bbPK/oWy6eThws7M3HI/X6mQ6NDQu9rkf5j0RpAkJAslDrr7+tP7yYmM+34mLfsNpqiggG0LfmHGxLHsWryQwrzyH/vqaEDwAGb1nYWngyffHvyWd3a8Q5Gx4nkzmxM2k1uUS696vcQaLMJtieDDzkJctJzIs87wcJP2nVFpHIjZuBZDkUjGszdvjYoiWSbbUP5LJ7VcHHDVqjibUvVPpLrTmTiUYvG4m8lGI0i3/+hy9a5FzyeeYtzUWbQe9ACGIj07/5jPjGfHsOP3uRTklD//prpp6duS+QPnE+wezNIzS3ly3ZNk6SqWpH5tZd3BDQdboou3KMjOE9NsqwERfNiZj0ZNqt46S6lrXVwI7dKdguwsjm60/HVdoey6ebqyJT2nQvuIDPDgdHIu+VZ63diCMVePwkmFVMoiddfTnzuHQ/Dda6c4e3jSffRYxk+dzT33PwTI7P77d2ZMHMvW+XPIyxTluQECXQOZO2Au7Wq3Y/+V/YxaOYrz2efLta/o5Gh2X95NuHc4LXxaWLajV53beAT/DiFW2bdgOyL4qASslfcBcM99D6FQqti1eCE6KxQcE8pGkiTCXRw5mlOxv4U5/6OERcOqCP35bDT13cr13KJLl1DVKf0UTic3d7oMf4xxU2fT4cHhKJQK9i1bzMznxrHpl5/JTU8rVz+qEzeNG9OjpjO08VDis+MZuXJkcdJoaZlkE98c+AaApyKfstoll4LLGfiHWW8WjWAbIvioBCTAZKUEKg8/f1r2G0R+ViZb5822ShtC2VS09geAQiHRqaE3206lWLBntmFIK0Dpqa3Qyak8z3V0caXjQyMZP3UOnYc9isrBgYOrljHzubGsn/kD2SlVN5izBLVCzXsd3uOV1q+Qrctm3NpxLD+zvNTP/+fUPxxMPsg9/vfQPbC71fop2bp0vWAVIvioBCJdHTlsxUWSOj48Enc/f45sWM3p/Xus1o5Qej293NhYgdofAN4uDng6aTidXLXyP4qS8tDUsV51zbtxcHKi3QMPM37qLLqNGoODswuH161k1gvjWfPjd2QmXbZb3+xNkiQej3icb7p/g0pS8eb2N/n+0PeY5DuPz57JPMNn+z5Do9DwTvt3rDbqkXU5HaVzzVjrqLoTwUcl4KNRk1Zkvev3Gq0j/Z95GYVSycrvvxRTbysBrVKBj0bFhQJdhfYTUdedsym55OmqRv6H/lIuav/yr0RrKixE0jhYpC8arSNtBg9h3NRZ9Hj8KZzcPTi6aS2zX3qKVVO/Ii0xwSLtVEW96vfil/6/4OPow89Hfub1ra+jM5b8Ws0szOTFTS9SYCjgjXZvEOQeZLV+nV2xj6ZDOlht/4LtiOCjkpBl2WqXXsC8PkavMRMoKixg8eT3SL900WptCaXTys2Z6JyCCtcsaOrvyp/7K/+JUpZljOmFqLzLv96HLi4Obahlkw3VGgda9R/M2O9mEjXuWVy9fTi2bRO/vPIMy6d8RsqFeIu2V1WEe4ezYOACmno2ZXX8asauGUtawY35MTn6HJ5a/xTx2fEMaTyEBxs/aNU+mXRFaF3Kt06SULlIciWr1pKdnY27uztZWVm4uZUvIa0qyigycDKvkHYe1h2O3vHHPHYvXoSTuwdD3ngfv+BSrAoqWE2a3sDxvAI6e7qW+bmnk3M4m5JHoJcTobUr/3tFF5+FqpYjShdNufeRu3UrLl27WrBXtzIaDBzftok9S/4ovgTTqG172g8ZViPfL3lFefxv6//YenErdV3qMq3XNBp6NORK3hUmbpxIXHocUfWi+KLbF6gU1psCezk2nvTjFwl/sLPV2hAqpiznbxF8VCJrU7PoU6v0a1yU167FC9n5x3xUag29n3qOsC49rN6mcHub0rJp7e6Mm6p0a1XEXsoiMaOAhr4uNPSxX+5EWcgmmcK4dBzDvCu0H1sEH9eYjEZO7NzK7n/+IP3qJZgGLdvQfsgw6jSpWVM9jSYjX+7/knnH5+GiduHZFs8yJ3YOyfnJ9Knfh8ldJqNRlj+oLI0DU1fQYkI/saZLJSaCjyrqeG4BTkoF9R0tc037To5t28S6n77HUKSnSbtO9Bo7ASd3D6u3K9xKlmWWp2Rxr6/HHbeJTsgkJUdHaG03Ar2q1tBz4ckMNEFuKDQVO3HYMvi4RjaZOLV3J7v//r04X6pesxZ0GDKMgLAIm/bF3hbFLWLy3snFCajjmo3juZbPobhD0TdLKMzN59j8LbR6qr9V2xEqxmbBx6effsqkSZN44YUXmDJlCgBPPfUU69ev59KlS7i4uNCxY0c+++wzQkJK902hJgcfACtSMhno42GTtpLjz7Jq2tekXohH4+hE28FDaDXwPjTa8l+TF8rnbL6OPKORZq43BhWyLLP3XDpZBUW0CPTA163qZfrLRUZ0Z7PQNvWq0H4MGRkUJSTgGBlpoZ6VjSzLnDmwl92LF3Hl7CkAAkIjaD9kGPWaNa8xpcR3JO7gt2O/MTJ0JF0DbBMIHvxpFU0f6oyzV9kvTwq2Y5PgY9++fTz88MO4ubnRo0eP4uDj559/JiQkhHr16pGens77779PdHQ0586dK9VwWU0PPo7nFqBWSDRyss1JxmgoYt/SxexdtpiiwgIcnJ2J6N6bZj374B0gCvnY0sqUTHp7u6NWSBhNMrvOpFFQZKRtkCceTtYd0ramgmNpaJt6ISkrdnLO27ULx9atUWjseyxkWSb+8EF2L17EpZPHAajduCnthwyjQcs2NSYIsZWc5AxOL9lDyyf72bsrwl1YPfjIzc2lVatW/PDDD3z00Ue0aNGiOPi42ZEjR2jevDmnT5+mYcOGFu18dWXL0Y9r8rMy2bv0L2I2ri1eBdSzTgDBLVtTp0kofsGNca1VC4VCXG+1Fp3JxLqULJwzizAaZdo39MbFoWqvYWHMK8JwJQ+HYI8K78sel1zuRJZlEmKPsHvxIhKOxQDg26Ah7Yc8QqM27ZEUYjKhJez/bjnNn+qH2kFt764Id2H14OOxxx7Dy8uLb775hu7du982+MjLy+Ptt99m6dKlxMXFoSnhG4tOp0On+2/+eHZ2NoGBgTU6+LhYqCdFb6Clm+2v6+sLC4jbvoUTu7aRcCwG+boVdxVKJS5e3mi0jqg0msrz4VpJvmlKlL8fJlkmp9BAors3vpKBWroKlF+vLMdDAm+jP2mKJCpwaIoZs7JRulfsM+GGT7ubPvrkmytn3vzRKN9+26TTJ29p69nZi9A6V42E4Mrqcmw8qUfO02x4N3t3RSiFsgQfZf5atWjRIg4ePMi+fftuu80PP/zA//73P/Ly8mjatCnr1q0rMfAAmDx5Mh988EFZu1GtBWg1xOYWkGc04mzjzG6N1pHIqH5ERvWjIDeHSyeOcenEcVITzpOVfIWctFRy0lJvCEoEy/FIOE1McDhNzh63xPnarpxUbuQr0sjQX7HcTqtI8VFJUlCkKxTBRwUYjUYurjpE21cfsHdXBCso08hHQkICbdq0Yd26dUReTfoqaeQjKyuL5ORkLl++zJdffkliYiI7duxAq701j0GMfJTMKMusuMsMCHuRZRmT0XDLF0O7qBSdKOFb811k5Ok5eD4DZwcV7Rp43bC6a3qRgbg8HR09ylEJtJIcD2QoPJ6BNtTTIrvTX7yIbDDgEBRUxm7It45IXf+/N40S3bqtdIf/vfkx6YZ/V5qRwSrq0Mw11OvVHO8G/vbuilBKVrvssmTJEh544IEbEkeNRiOSJKFQKNDpdLckler1ejw9PZk5cybDhw+3aOeru/MFOtL0Blq5l78ctVC5JGUVcuRiJp7OGtrU97xtcuLm9GxauZW+9kdlU5SUB0oJtY9lLh3mbtuGc6dO4oReQ1zYe4Kss1doNqzy5PgId2e1yy69evUiJibmhvueeOIJQkJCeP3110uczSLLMrIs3zC6IZROfUcHLhToSdIV4S+Sraq0C2n5xCVl4+empU/43b/JdfN05d+ULAZXwpGv0jCkFuAYUctyO5RlEXjUEAXZeVzZfpy2L99v764IVlSm4MPV1ZWIiBuL6jg7O+Pt7U1ERARnz57l999/p0+fPvj4+HDx4kU+/fRTHB0dGTBggEU7XlN08XJlWXImUd5uOCnFh29Vc+pKDmdT86jn5VSqoOMaSZIId3HkaE4+Ea5Vq6CY7nw2mno1e9RSKB+j0cjRH1fTfOIge3dFsDKLns20Wi3btm1jwIABNGrUiEceeQRXV1d27tyJr6+vJZuqUQb5uLMqJdOqC88JlnU0MYu1sUkoFRJ9w/3LtfZKsJMDCYV6ikxV5+8um2RMuXqUbparxSEXFYEoqV0jHJq2kkYjuqJxsn6VZ8G+RHn1KiLPYGRdWjb3+XqIIkaVlCzLHLyQSVqujrA6bgR4VnzEQmcysTk9h742WPPHEgpPZaAJdEWhtVx9koLYWNS+vqh8fCy2T6HyiZ6zDs+wQOq3q1nr5lQnZTl/i3H8KsJZpaSHlyvLUjIrvAS7YFmyLLP7bBprj10h0MuRPuH+Fgk8ABwUCnw1ai4UVP6cKdlgQjbKFg08AIxpaSLwqOaiZ6/FrVEdEXjUIFW7fGIN465W0dPLjWUpmdzrI0ZA7M1oktl5JpUCvZF2Dbxxd7JOUnBLNyeWJWcSqNVU6r954akMtI0tM7VWqDkOzliNd7P61G8fau+uCDYkgo8qxlWlpJeXG0uSMxng446DmAFgc3qDiR1nUjEaZTo09MbZBiXQO3m4sCMzl86elXNhLVOhAUmtQFKJ16NQOkajkegfVuHTrjH17mlq7+4INiaCjyrIRaVkkI8HK1Mz6eDugq+YhmsTBXojO8+kopAkOjT0Rqu2XRKkt0aFIVcmq8iAu7ryvW11ZzLRhnpbfL/G3FwUzqLOTXWTl57DsZlrafhwF7yCxGSEmqjyfYoJpaJWSNzn68nW9BzSigyEujjau0vVVnZhEXvOpuOgUtCtiQ8qO0157ubpyvJKWPXWmKVD4aq5oUqrpeiOH0cbFmbx/Qr2c/HQaZI2x9LihXvFYnE1mAg+qriuXq4czy1gdUoWUd5uqKxwAqip0nJ17D+fgatWRa8QXxR2PraSJBHh4khMTj7NKlHtD31CjmULil3HVFAgRj6qCaPRSMyvG5DUKtq8dJ+9uyPYmQg+qoFQF0caODqwJi2LJk5aGjvfuoaOUHqXswo4cjELb2cNfcL8KlWSZ7CTAytTMglxdkRdCQLNouR8VD5i1E24s8ux8VxcfYj6g9vi2yTA3t0RKgERfFQTWqWCgT4eHMstYGVKJl09XXGpouuC2Et8ah4nruRQ211L3zJUI7W1Xt5ubEjLpp+P/Wt/GJLzrTbqIVR9+nwdMb9uQOWipe0rYnVa4T8i+KhmwlwcCXHWsi0jF73JRDcvVzRiRswdnbySQ3xqHvW8nSp10HGNg0KBr4OKCwU66jnarxKkPiEHdYD1Zt8UXbmCys/PavsXrMdoNBIzdxPGXB0hI7ri7FU5Z2kJ9iOCj2pIIUl083JFZzKxJT0HhSTR0cMFR7E2zA1iLmZxKauAxr4uZVp3pTJo5eZs19ofsixjzNKhCbTeSUV36jTO7dtZbf+C5RXpiji2aCtFWfkE39tOzGQRbksEH9WYg0JB71ru6E0mdmXmUWgyEebiSKDWcutuVDXmEugZpObqiajrTrMA+1+6KK/Onvar/aE7m4VDsJWPncmIpBIfUVVB2rkk4lccQFJC8L3t8KgrLsUJdybe2TWARqGg29Vhz6M5+cTlFiBJEi1cnailqRkvAZNJZs+5dLILi2hVz5PW9b3s3aUK81KrMMrYvPaHbDQh64worFTRVagasq9kcHrZHjAYUbk60fzJvqhqyOeJUHHilVLDRLg6EeEKJlkmOiefQ9l5SJKEl1pJhItjtcsPMRhN7DqbZvUS6PbS1dOFf1OyGGzD2h+FpzKtXkZdNhpBql6vxarOoDdwduNhcs5dAZMJlYsjYcO7onWpPNO+hapDBB81lEKSaOX2X/2ENL2B3Zl56GUZCZAArUJBfUcNtR3UKCrRdNPS0BmM7DyTZtMS6PZg69ofJp0RSSEhqa0bGOjPnsUhuIFV2xBKZjQaSTmRSMrhcxRl5xcvZKlQKPBp3ZAm/VrbuYdCdVA9P5GFMvPWqOh6U0Z6vtHEhUIdpzIKuX4h3Wv/rKzhiEmWWX00CX93R1RKidgTl+3dJaszyDLpjtavt+GQUoCy0Ih8MdOq7SiTklHkZAMxVm0HML+QS1oo+toLvCyPXf+mKO1jN7+R7vQGK8eb73arYMuyfNtkZcfangR0CcMzQKwmLFiHJFey9dmzs7Nxd3cnKysLNzc3e3dHEARBEIRSKMv5W1xUFQRBEATBpkTwIQiCIAiCTYngQxAEQRAEmxLBhyAIgiAINiWCD0EQBEEQbEoEH4IgCIIg2JQIPgRBEARBsCkRfAiCIAiCYFMi+BAEQRAEwaZE8CEIgiAIgk2J4EMQBEEQBJsSwYcgCIIgCDYlgg9BEARBEGxKBB+CIAiCINiUyt4duJksy4B5aV5BEARBEKqGa+fta+fxO6l0wUdOTg4AgYGBdu6JIAiCIAhllZOTg7u7+x23keTShCg2ZDKZuHTpEq6urkiSZLd+ZGdnExgYSEJCAm5ubnbrR00hjrftiWNue+KY25Y43rYlyzI5OTnUqVMHheLOWR2VbuRDoVAQEBBg724Uc3NzEy9aGxLH2/bEMbc9ccxtSxxv27nbiMc1IuFUEARBEASbEsGHIAiCIAg2JYKP23BwcOC9997DwcHB3l2pEcTxtj1xzG1PHHPbEse78qp0CaeCIAiCIFRvYuRDEARBEASbEsGHIAiCIAg2JYIPQRAEQRBsSgQfgiAIgiDYlAg+SnDw4EF69+6Nh4cH3t7ePPnkk+Tm5t6wzb59++jVqxceHh54enrSt29fDh8+bKceV22lOd4Av/zyC5GRkWi1Wnx9fXn22Wft0NvqobTHHCAtLY2AgAAkSSIzM9O2Ha0m7na8Dx8+zPDhwwkMDMTR0ZHQ0FC+/fZbO/a46ivNa/zChQsMHDgQJycnfH19ee211zAYDHbqcc0igo+bXLp0iaioKBo1asSePXtYvXo1sbGxPP7448Xb5Obm0q9fP+rVq8eePXvYvn07rq6u9O3bl6KiIvt1vgoqzfEG+Prrr3nrrbd44403iI2NZf369fTt29c+na7iSnvMrxk7diyRkZG27WQ1UprjfeDAAXx9fZk3bx6xsbG89dZbTJo0ialTp9qv41VYaY650Whk4MCB6PV6du7cya+//sovv/zCu+++a7+O1ySycIOffvpJ9vX1lY1GY/F9R44ckQH51KlTsizL8r59+2RAvnDhwm23EUqnNMc7PT1ddnR0lNevX2+vblYrpTnm1/zwww9yt27d5A0bNsiAnJGRYePeVn1lOd7Xe+aZZ+QePXrYoovVTmmO+cqVK2WFQiEnJSUVbzN9+nTZzc1N1ul0Nu9zTSNGPm6i0+nQaDQ3LIrj6OgIwPbt2wFo2rQp3t7ezJo1C71eT0FBAbNmzSI0NJSgoCB7dLvKKs3xXrduHSaTicTEREJDQwkICODhhx8mISHBLn2u6kpzzAGOHTvGhx9+yG+//XbXRaKE2yvt8b5ZVlYWXl5eVu9fdVSaY75r1y6aNWuGn59f8TZ9+/YlOzub2NhY23a4BhKfKDfp2bMnSUlJfPHFF+j1ejIyMnjjjTcAuHz5MgCurq5s3ryZefPm4ejoiIuLC6tXr2bVqlWoVJVurb5KrTTH++zZs5hMJj755BOmTJnCX3/9RXp6Or1790av19uz+1VSaY65Tqdj+PDhfPHFF9SrV8+e3a3ySnO8b7Zz505+//13nnzySVt2tdoozTFPSkq6IfAAiv8/KSnJth2ugWpM8PHGG28gSdIdb3FxcYSHh/Prr7/y1Vdf4eTkhL+/Pw0aNMDPz684ii4oKGDs2LF06tSJ3bt3s2PHDiIiIhg4cCAFBQV2/k0rB0seb5PJRFFREd999x19+/alffv2LFy4kFOnTrFp0yY7/6aVhyWP+aRJkwgNDWXUqFF2/q0qL0se7+sdPXqU++67j/fee48+ffrY4TervKx1zAXbqzHl1VNSUkhLS7vjNsHBwWg0muL/v3LlCs7OzkiShJubG4sWLeKhhx5i1qxZvPnmm1y+fLn4hazX6/H09GTWrFkMGzbMqr9LVWDJ4z1nzhzGjBlDQkICAQEBxdv7+fnx0UcfMX78eKv9HlWJJY95ixYtiImJQZIkAGRZxmQyoVQqeeutt/jggw+s+rtUBZY83tccO3aMHj16MG7cOD7++GOr9b2qsuQxf/fdd1m2bBnR0dHF2547d47g4GAOHjxIy5YtrfVrCECNuUbg4+ODj49PmZ5zbQhu9uzZaLVaevfuDUB+fj4KhaL4gxko/n+TyWS5TldhljzenTp1AuDEiRPFwUd6ejqpqanUr1/fgr2u2ix5zBcvXnzDKN6+ffsYM2YM27Zto2HDhpbrdBVmyeMNEBsbS8+ePXnsscdE4HEbljzmHTp04OOPPyY5ORlfX1/AnF/m5uZGWFiYZTsu3MrOCa+V0vfffy8fOHBAPnHihDx16lTZ0dFR/vbbb4sfP378uOzg4CBPmDBBPnbsmHz06FF51KhRsru7u3zp0iU79rxqutvxlmVZvu++++Tw8HB5x44dckxMjDxo0CA5LCxM1uv1dup11VaaY369TZs2idkuFXC34x0TEyP7+PjIo0aNki9fvlx8S05OtmOvq7a7HXODwSBHRETIffr0kaOjo+XVq1fLPj4+8qRJk+zY65pDBB8lGD16tOzl5SVrNBo5MjJS/u23327ZZu3atXKnTp1kd3d32dPTU+7Zs6e8a9cuO/S26ivN8c7KypLHjBkje3h4yF5eXvIDDzxww1RnoWxKc8yvJ4KPirnb8X7vvfdk4JZb/fr17dPhaqA0r/H4+Hi5f//+sqOjo1yrVi35lVdekYuKiuzQ25qnxuR8CIIgCIJQOYi0X0EQBEEQbEoEH4IgCIIg2JQIPgRBEARBsCkRfAiCIAiCYFMi+BAEQRAEwaZE8CEIgiAIgk2J4EMQBEEQBJsSwYcgCIIgCDYlgg9BEARBEGxKBB+CIAiCINiUCD4EQRAEQbApEXwIgiAIgmBT/w8fdLhKZCIy8gAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SKIP FOR OPTION 3. Continuing w/option 1 - set the cluster area thresholds to unitize cluster use\n",
    "print(\"default use fraction for corner clusters is 1.00, but can enter higher number to account for later discontig rejects\")\n",
    "print(\"for MN, I suggest 1.3, 1.05, 1.3, 1.05\")\n",
    "CCBuse, CCBareaFrac, CCBarea = [0. for CCB in CCBlist], [0.5 for CCB in CCBlist], [geo.area for geo in CCBgeom]\n",
    "for j,geo in enumerate(CCBgeom):\n",
    "    maxCCBfrac = float(input(\"enter maxCCBfrac (e.g. 1.0) prior to discontig shedding\"))\n",
    "    nIntersections = 0\n",
    "    print(\"working on cluster no\",j,\"containing counties\",CCBlist[j] )\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    HDfrac = [ 0. for t in range(nHDs) ]\n",
    "    for t in range(nHDs):\n",
    "        if HDcountyNo[t] in CCBlist[j]:\n",
    "            HDfrac[t] = 1.\n",
    "        else:\n",
    "            HDfrac[t] = HDpoly[t].intersection(geo).area / CCBarea[j]\n",
    "    idx = np.argsort(HDfrac)\n",
    "    i = nHDs\n",
    "    while CCBuse[j] < maxCCBfrac - 0.5 * nDistricts*np.average(HDweight) and i > 0:  #maxCCBfrac vs. 1.0\n",
    "        i -=1\n",
    "        nIntersections +=1\n",
    "        t = idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        if CCBuse[j] > 0.5 and CCBuse[j] - HDweight[t] * nDistricts < 0.5:\n",
    "            print(\"halfway there! last use was\",r5(HDfrac[t]))\n",
    "            plotPoly(HDpoly[t].intersection(MAP.buffer(1)),0.2)\n",
    "        #origHDlist[t].append(unitNo)  #postpone this until main loop\n",
    "        #origHDpop[t] += CCBpop[j]     #postpone until main\n",
    "    if i <= 1:\n",
    "        print(\"WARNING, only\",r5(CCBuse[j]),\" of a district's worth of ensemble intersected the cluster geometry\")\n",
    "        # Add more stuff here to inflate the poly and try again ...\n",
    "    else:\n",
    "        CCBareaFrac[j] = HDfrac[t]\n",
    "        print(\"our final fractional capture area to normalize this cluster's usage is\",r5(CCBareaFrac[j]),\"from\",nIntersections,\"intersecting HDs\" )\n",
    "        plotPoly(geo,0.8)\n",
    "        plotCenter(j,geo)\n",
    "        plotPoly(HDpoly[t].intersection(MAP.buffer(0.5)),1.3)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "id": "217527a2-0acf-43ec-9a25-09e0aecce76d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This is the main code to determine each HD's pop based on UNIT CP's that intersect the HDpoly\n",
      "We'll later add nearby or jettison faraway contiguous units until we approach the aDP\n",
      "  the HD pops and lists already appropriately include captured corner county clusters\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to enforce areaFrac threshold capture for clusters; helps to even up their usage 1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on HDno 0 time in sec is now 0\n",
      "working on HDno 513 time in sec is now 201\n",
      "working on HDno 1015 time in sec is now 388\n",
      "working on HDno 1520 time in sec is now 422\n",
      "working on HDno 2028 time in sec is now 555\n",
      "working on HDno 2530 time in sec is now 660\n",
      "working on HDno 3032 time in sec is now 819\n",
      "working on HDno 3535 time in sec is now 831\n",
      "working on HDno 4038 time in sec is now 854\n",
      "all done assigning units to HDs based on original HD polygons\n",
      "Here is a scatterplot of active HD pop excess vs relative to target 713311.75\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, compute the current unit usage, plot its histogram weighted by unit pop\n",
      "unit avg and sd usage are 0.98057 0.15353\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to correcting for discontiguity ...\n",
      "CCB cluster 0 with pop 314005.0 originally had use of 1.2304115276385004\n",
      "CCB cluster 1 with pop 148064.0 originally had use of 0.902214214191733\n",
      "CCB cluster 2 with pop 216736.0 originally had use of 1.1111410964420292\n",
      "CCB cluster 3 with pop 65226.0 originally had use of 0.9915229911745908\n"
     ]
    }
   ],
   "source": [
    "#continuing w/option 1 - now we determine 12-wedge-capture (frag) vtd lists for the original HD polygons\n",
    "# FOR MD, THIS IS VERY SLOW.  Slow also for MI.  Starting w/MN, we stopped enforcing contiguity on clusterswell\n",
    "print(\"This is the main code to determine each HD's pop based on UNIT CP's that intersect the HDpoly\")\n",
    "print(\"We'll later add nearby or jettison faraway contiguous units until we approach the aDP\")\n",
    "print(\"  the HD pops and lists already appropriately include captured corner county clusters\")\n",
    "#see above block for preliminaries\n",
    "nonUnitCounties = list (set([c for c in range(nCounties)]).difference(set(unitCounties)) )\n",
    "areaFrac = [0.5 for u in range(nUnits)]  #default; we will accept unit counties if we capture half their area\n",
    "alter = input(\"enter 1 to enforce areaFrac threshold capture for clusters; helps to even up their usage\")\n",
    "if alter == 1:\n",
    "    for u in range(nUnits):\n",
    "        if allUnits[u] - int(allUnits[u]) == 0.25:  #a county cluster.  Enforce alternate areaFrac's determined above\n",
    "            CCBno = int(allUnits[u] )\n",
    "            areaFrac[u] = CCBareaFrac[CCBno ]\n",
    "            print(\"enforcing areaFrac capture threshold of\",r5(CCBareaFrac[CCBno]),\"for CCBno, uNo\",CCBno,u)\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] - int(allUnits[u]) == 0.25:  #a county cluster.  Enforce alternate areaFrac's determined above\n",
    "        CCBno = int(allUnits[u] )\n",
    "        areaFrac[u] = CCBareaFrac[CCBno ]\n",
    "        #print(\"enforcing areaFrac capture threshold of\",r5(CCBareaFrac[CCBno]),\"for CCBno, uNo\",CCBno,u)\n",
    "# for c in unitCounties:   #UNCOMMENT TO ENFORCE UNIT COUNTIES TO EQUAL USAGE\n",
    "#    areaFrac[allUnits.index(c+0.5)] = unitCareaFrac[ unitCounties.index(c) ]\n",
    "\n",
    "origHDpop, origHDlist = [0. for t in range(nHDs)], [list() for t in range(nHDs)]\n",
    "\n",
    "startTime = time.time()\n",
    "for jj,t in enumerate(popHDlist):\n",
    "    if jj%500 == 0:\n",
    "        print(\"working on HDno\",t, \"time in sec is now\",int(time.time()-startTime) )\n",
    "    hC = HDcountyNo[t]\n",
    "    if hC in allFusedCounties:  #using a swelling technique as original HDpoly's look skewy\n",
    "    #if STATE != \"MD\" and hC in allFusedCounties:\n",
    "        origHDpop[t], origHDlist[t] = clusterSwell(hdCP[t], CCBgeom, CCBpop, allUnits, unitCP, unitPop, unitNbrs, borderUnits,aDP)\n",
    "    else:\n",
    "        if hC in unitCounties:\n",
    "            iCP, iClist = countyPop[hC], [allUnits.index(hC+0.5) ] #automatically include the home county if small\n",
    "        else: #must probe in-county list vs HDpoly intersxn\n",
    "            iCP, iClist =  getPolyPop(HDpoly[t], unitCP, unitPop, countyUnitList[hC])\n",
    "        nonCP, nonClist = getNonHCunits(HDpoly[t], hC, allUnits, unitCP, unitPop, allFusedCounties, areaFrac, countyGeom,\n",
    "                                        neighborCountyList, countyUnitList)  #this will miss county clusters; see below\n",
    "        origHDpop[t]  += iCP + nonCP\n",
    "        origHDlist[t] += iClist + nonClist\n",
    "        for j, geo in enumerate(CCBgeom):  #special for corner clusters -- intersection area must clear threshold estbd in a prev block ...\n",
    "            unitNo = allUnits.index(j+0.25)\n",
    "            if geo.intersection(HDpoly[t]).area >= areaFrac[unitNo] * CCBarea[j]: #we probably should also add a contigy criterion here \n",
    "                origHDpop[t] += unitPop[unitNo]\n",
    "                origHDlist[t].append(unitNo)\n",
    "print(\"all done assigning units to HDs based on original HD polygons\")\n",
    "HDpopExcess = list()\n",
    "for t in popHDlist:\n",
    "    HDpopExcess.append(origHDpop[t] - aDP)\n",
    "print(\"Here is a scatterplot of active HD pop excess vs relative to target\",aDP)\n",
    "plt.scatter(popHDlist, HDpopExcess)\n",
    "plt.axhline(-0.01*aDP,np.min(popHDlist),np.max(popHDlist),ls=\"--\")\n",
    "plt.axhline( 0.01*aDP,np.min(popHDlist),np.max(popHDlist),ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, compute the current unit usage, plot its histogram weighted by unit pop\")\n",
    "origUnitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in origHDlist[t]:\n",
    "        origUnitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(origUnitUse,bins=50,weights=unitPop)\n",
    "origUnitUseAvg, origUnitUseSD = getWeightedAvgAndSD(origUnitUse,unitPop)\n",
    "print(\"unit avg and sd usage are\",r5(origUnitUseAvg), r5(origUnitUseSD) )\n",
    "plt.show()\n",
    "print(\"prior to correcting for discontiguity ...\")\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"with pop\",unitPop[u],\"originally had use of\",origUnitUse[u])\n",
    "\n",
    "HDunitList = [origHDlist[t].copy() for t in range(nHDs) ]  #for safekeeping\n",
    "HDvPop = origHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "0fdec9f3-be08-4952-9745-bb0e47e5a04d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are your HDs with sig devn from target pops\n",
      "The total number of HDs under, over target pop by 0.3 are 52 139\n"
     ]
    }
   ],
   "source": [
    "nUnder, nOver, thresh = 0,0, 0.3\n",
    "print(\"here are your HDs with sig devn from target pops\")\n",
    "for t in popHDlist:\n",
    "    if HDvPop[t] < (1. - thresh) * aDP:\n",
    "        nUnder +=1\n",
    "        #print(t,r3(HDvPop[t]/aDP))  #uncomment if a small number\n",
    "    if HDvPop[t] > (1. + thresh) * aDP:\n",
    "        nOver +=1\n",
    "        #print(t,r3(HDvPop[t]/aDP))\n",
    "print(\"The total number of HDs under, over target pop by\",thresh,\"are\",nUnder, nOver)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 174,
   "id": "8d5f678f-c2df-4ee7-bafe-fd75ba2cb42e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "alternate to above = 'option3' - create HDunitLists based on each HD's tractList\n"
     ]
    }
   ],
   "source": [
    "#OPTION 3 - ALTERNATE TO ABOVE THREE BLOCKS\n",
    "print(\"alternate to above = 'option3' - create HDunitLists based on each HD's tractList\")\n",
    "HDtractListString = shapeDF[\"HDtractList\"]\n",
    "HDtractList = [ast.literal_eval(HDtractListString[t]) for t in range(nHDs)]\n",
    "CCBpopFrac = [[0. for j in range(len(CCBgeom)) ]  for t in range(nHDs)]\n",
    "\n",
    "nCCBs = len(CCBlist)\n",
    "unitParentVTDno = [-999 for u in range(nUnits)]\n",
    "for u in range(nUnits):    \n",
    "    if allUnits[u] %1 == 0:\n",
    "        v = allUnits[u]\n",
    "        unitParentVTDno[u] = parentVTDno[v]\n",
    "              "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "id": "ec034144-b3dc-4b72-9350-6d85cabcb8a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\n",
      "working on vtd --> unit conversion for HD 1 last HD had pop 653678.408\n",
      "working on vtd --> unit conversion for HD 601 last HD had pop 712982.4\n",
      "working on vtd --> unit conversion for HD 1201 last HD had pop 645274.504\n",
      "working on vtd --> unit conversion for HD 1801 last HD had pop 525893.357\n",
      "working on vtd --> unit conversion for HD 2401 last HD had pop 472855.0\n",
      "working on vtd --> unit conversion for HD 3001 last HD had pop 712813.0\n",
      "working on vtd --> unit conversion for HD 3601 last HD had pop 720195.22\n"
     ]
    }
   ],
   "source": [
    "print(\"Now assigning each HD's units (excluding CCB's) based on the captured whole vtd's\" )\n",
    "HDunitList = [ list() for t in range(nHDs) ]\n",
    "for t in range(nHDs):\n",
    "    if t %600 == 1:\n",
    "        print(\"working on vtd --> unit conversion for HD\",t,\"last HD had pop\",r3( np.sum([unitPop[u] for u in HDunitList[t-1]]) ) )\n",
    "    capturedCountyPop = [0. for c in range(nCounties)]\n",
    "    capturedCCBpop = [0. for i in range(nCCBs)]\n",
    "    for v in HDtractList[t]:\n",
    "        c = HDcountyNo[v]\n",
    "        if c in range(nCounties):  #we assigned countyno = -999 to unpopulated tracts\n",
    "            if c in unitCounties:\n",
    "                capturedCountyPop[c] += tractPop[v]\n",
    "            elif c in allFusedCounties:\n",
    "                for i, L in enumerate(CCBlist):\n",
    "                    if c in L:\n",
    "                        capturedCCBpop[i] += tractPop[v]\n",
    "            else:  #this vtd not part of a unit or fused county.  Could be split into fragments\n",
    "                for u in countyUnitList[c]:\n",
    "                    if unitParentVTDno[u] == v :  #we assign all units = vtd fragments from this HDTL-captured vtd\n",
    "                        HDunitList[t].append(u)\n",
    "    for c in unitCounties:\n",
    "        if capturedCountyPop[c] > 0.5 * countyPop[c]:\n",
    "            HDunitList[t].append(allUnits.index(c+0.5))\n",
    "    for i in range(nCCBs):  #don't yet assign in/out CCBs.  We'll do so in below block\n",
    "        CCBpopFrac[t][i] = capturedCCBpop[i] / CCBpop[i]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "1494814c-7b90-425c-b8b1-3a2006bdeb2d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\n",
      "CCBno 0 with pop 314005.0 would be used 1.7170570931994222 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 1 with pop 148064.0 would be used 1.3227638546539668 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 2 with pop 216736.0 would be used 1.5752046703281914 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n",
      "CCBno 3 with pop 65226.0 would be used 1.2466821133956922 if we added it to all adjoining districts\n",
      "Here is the histogram of relative district pop with these added\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CCBno 0 with pop 314005.0 would be used 1.7170570931994222 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 1 with pop 148064.0 would be used 1.3227638546539668 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 2 with pop 216736.0 would be used 1.5752046703281914 if we added it to all adjoining districts with no 2-CCB districts\n",
      "CCBno 3 with pop 65226.0 would be used 1.2466821133956922 if we added it to all adjoining districts with no 2-CCB districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option 3.  Determine each CCB's use if we add it to all adjoining HDs\")\n",
    "CCBwouldUse = [0. for i in range(nCCBs)]\n",
    "CCBaddCandidates = [list() for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    jNo = allUnits.index(j+0.25)\n",
    "    ccbNbrSet = set(unitNbrs[jNo])\n",
    "    withCCBpopRat = list()\n",
    "    for t in range(nHDs):\n",
    "        if len(ccbNbrSet.intersection(set(HDunitList[t]))) > 0:\n",
    "            CCBwouldUse[j] += HDweight[t] * nDistricts\n",
    "            CCBaddCandidates[j].append(t)\n",
    "            withCCBpopRat.append((np.sum([unitPop[u] for u in HDunitList[t]]) + CCBpop[j]) / aDP )\n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",CCBwouldUse[j],\"if we added it to all adjoining districts\")\n",
    "    print(\"Here is the histogram of relative district pop with these added\")\n",
    "    plt.hist(withCCBpopRat,histtype=\"step\",label=j)\n",
    "plt.legend()\n",
    "plt.show()\n",
    "\n",
    "for j in range(nCCBs):    \n",
    "    jNo = allUnits.index(j+0.25)\n",
    "    for jj in range(jj+1, nCCBs):\n",
    "        jjNo = allUnits.index(j+0.25)\n",
    "        for t in CCBaddCandidates[j].copy():\n",
    "            if t in CCBaddCandidates[j]:\n",
    "                if t in CCBaddCandidates[jj].copy():\n",
    "                    dist_j, dist_jj = hdCP[t].distance(unitCP[jNo]), hdCP[t].distance(unitCP[jjNo])\n",
    "                    if dist_j > dist_jj:\n",
    "                        CCBaddCandidates[j].remove(t)  #for MN, don't allow any districts with two CCB's\n",
    "                        CCBwouldUse[j] -= HDweight[t] * nDistricts\n",
    "                    else:\n",
    "                        CCBaddCandidates[jj].remove(t)\n",
    "                        CCBwouldUse[jj] -= HDweight[t] * nDistricts\n",
    "for j in range(nCCBs):    \n",
    "    print(\"CCBno\",j,\"with pop\",CCBpop[j],\"would be used\",CCBwouldUse[j],\"if we added it to all adjoining districts with no 2-CCB districts\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 177,
   "id": "707c2ab8-1006-4ae3-9e17-5ca30c80259e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\n",
      "final unit use of CCB 0 is 1.00484\n",
      "final unit use of CCB 1 is 1.00024\n",
      "final unit use of CCB 2 is 1.00214\n",
      "final unit use of CCB 3 is 1.00185\n"
     ]
    }
   ],
   "source": [
    "print(\"Continuing option 3. Now assign CCB units.  For each, work from most to least underpopped\")\n",
    "#previously, we went from most-used to least-used CCB vtds until each has unit use\")\n",
    "CCBuse = [0. for i in range(nCCBs)]\n",
    "for j in range(nCCBs):\n",
    "    unitNo = allUnits.index(j+0.25)\n",
    "    #ccbNbrSet = set(unitNbrs[unitNo])\n",
    "    #ccbFrac = [-1.*CCBpopFrac[t][j] for t in range(nHDs) ]  # -1 to go from most- to least-used\n",
    "    #idx = np.argsort(ccbFrac)\n",
    "    preCCBpop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in CCBaddCandidates[j]]\n",
    "    idx = np.argsort(preCCBpop)\n",
    "    i = 0\n",
    "    t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "    while CCBuse[j] < 1.00  and i < len(CCBaddCandidates[j]) :  #and CCBpopFrac[t][j] > 0:\n",
    "        t = CCBaddCandidates[j][idx[i]] #idx[i]\n",
    "        CCBuse[j] += HDweight[t] * nDistricts\n",
    "        HDunitList[t].append(unitNo)\n",
    "        i +=1\n",
    "    unitUse[unitNo] = CCBuse[j]\n",
    "    print(\"final unit use of CCB\",j, \"is\",r5(CCBuse[j]))\n",
    "        \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf747d9c-cf6d-420e-9c3c-6723619586ac",
   "metadata": {},
   "outputs": [],
   "source": [
    "#end of preiminaries for \"option 3\" - converting HDtractlists to unit lists instead of option 2's geometric probing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "26102ca2-79c1-48db-b873-7fa3a1553911",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "dc26d08c-a5d9-4e7e-9da5-ae98cf658a3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here is the histogram of HD pops relative to aDP\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "orig unit avg and sd usage are 1.02148 0.13367\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs) ]\n",
    "print(\"Here is the histogram of HD pops relative to aDP\")\n",
    "plt.hist([HDvPop[t] / aDP for t in range(nHDs) ], bins=20, label= \"HDpop / target\" )\n",
    "plt.show()\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "id": "c4183011-724a-4014-8c94-f9f9382c7e75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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RYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANZpkwDz6aef6ic/+Ym6d++u1NRUDR48WGvXrnXajTGaOXOmsrKylJqaqlAopG3btsUto6KiQkVFRfJ6vfL7/Ro3bpyqqqraorsAAMAyCQ8w+/bt04UXXqhOnTrp1Vdf1ebNm/Vf//Vf6tatm1MzZ84czZ07V/PmzVNJSYm6dOmigoICHTx40KkpKirSpk2btHjxYi1cuFArV67UhAkTEt1dAABgIZcxxiRygdOmTdNbb72lN954o8l2Y4yys7N122236Ze//KUkKRKJKBAIaP78+RozZoy2bNmigQMHas2aNRo+fLgkadGiRbriiiv0ySefKDs7+6j9iEaj8vl8ikQi8nq9idtAAADQZlp7/E74GZiXXnpJw4cP17/+678qMzNT5557rv70pz857du3b1c4HFYoFHLm+Xw+5eXlqbi4WJJUXFwsv9/vhBdJCoVCcrvdKikpaXK91dXVikajcRMAADg5JTzAfPzxx3r00UfVr18//fOf/9TNN9+s//iP/9CTTz4pSQqHw5KkQCAQ975AIOC0hcNhZWZmxrUnJycrIyPDqTnSrFmz5PP5nCknJyfRmwYAADqIhAeYWCymoUOH6t5779W5556rCRMmaPz48Zo3b16iVxVn+vTpikQizrRr1642XR8AAGg/CQ8wWVlZGjhwYNy8AQMGaOfOnZKkYDAoSSorK4urKSsrc9qCwaDKy8vj2mtra1VRUeHUHMnj8cjr9cZNAADg5JTwAHPhhRdq69atcfM++OAD9enTR5KUm5urYDCopUuXOu3RaFQlJSXKz8+XJOXn56uyslKlpaVOzbJlyxSLxZSXl5foLgMAAMskJ3qBt956qy644ALde++9uvbaa7V69Wo9/vjjevzxxyVJLpdLkydP1j333KN+/fopNzdXM2bMUHZ2tkaNGiWp/oxNYWGh89VTTU2NJk2apDFjxrTqDiQAAHByS/ht1JK0cOFCTZ8+Xdu2bVNubq6mTJmi8ePHO+3GGN111116/PHHVVlZqYsuukiPPPKIzjjjDKemoqJCkyZN0ssvvyy3263Ro0dr7ty5Sk9Pb1UfuI0aAAD7tPb43SYBpiMgwAAAYJ92ew4MAABAWyPAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWKfNA8zs2bPlcrk0efJkZ97Bgwc1ceJEde/eXenp6Ro9erTKysri3rdz505deeWVSktLU2Zmpm6//XbV1ta2dXcBAIAF2jTArFmzRo899pjOPvvsuPm33nqrXn75ZT3//PNasWKFdu/erWuuucZpr6ur05VXXqlDhw5p1apVevLJJzV//nzNnDmzLbsLAAAs0WYBpqqqSkVFRfrTn/6kbt26OfMjkYj+/Oc/64EHHtB3v/tdDRs2TE888YRWrVqlt99+W5L02muvafPmzfrb3/6mc845R5dffrnuvvtuPfzwwzp06FBbdRkAAFiizQLMxIkTdeWVVyoUCsXNLy0tVU1NTdz8M888U71791ZxcbEkqbi4WIMHD1YgEHBqCgoKFI1GtWnTpibXV11drWg0GjcBAICTU3JbLPSZZ57RunXrtGbNmkZt4XBYKSkp8vv9cfMDgYDC4bBTc3h4aWhvaGvKrFmz9Nvf/jYBvQcAAB1dws/A7Nq1S7/4xS/01FNPqXPnzolefLOmT5+uSCTiTLt27Tph6wYAACdWwgNMaWmpysvLNXToUCUnJys5OVkrVqzQ3LlzlZycrEAgoEOHDqmysjLufWVlZQoGg5KkYDDY6K6khtcNNUfyeDzyer1xEwAAODklPMBcdtll2rBhg9avX+9Mw4cPV1FRkfPvTp06aenSpc57tm7dqp07dyo/P1+SlJ+frw0bNqi8vNypWbx4sbxerwYOHJjoLgMAAMsk/BqYrl27atCgQXHzunTpou7duzvzx40bpylTpigjI0Ner1e33HKL8vPzdf7550uSRo4cqYEDB+qGG27QnDlzFA6Hdeedd2rixInyeDyJ7jIAALBMm1zEezT//d//LbfbrdGjR6u6uloFBQV65JFHnPakpCQtXLhQN998s/Lz89WlSxeNHTtWv/vd79qjuwAAoINxGWNMe3eiLUSjUfl8PkUiEa6HAQDAEq09fvO3kAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANZJeICZNWuWzjvvPHXt2lWZmZkaNWqUtm7dGldz8OBBTZw4Ud27d1d6erpGjx6tsrKyuJqdO3fqyiuvVFpamjIzM3X77bertrY20d0FAAAWSniAWbFihSZOnKi3335bixcvVk1NjUaOHKkvvvjCqbn11lv18ssv6/nnn9eKFSu0e/duXXPNNU57XV2drrzySh06dEirVq3Sk08+qfnz52vmzJmJ7i4AALCQyxhj2nIFe/fuVWZmplasWKFLLrlEkUhEPXv21N///nf96Ec/kiS9//77GjBggIqLi3X++efr1Vdf1fe//33t3r1bgUBAkjRv3jxNnTpVe/fuVUpKylHXG41G5fP5FIlE5PV623ITAQBAgrT2+N3m18BEIhFJUkZGhiSptLRUNTU1CoVCTs2ZZ56p3r17q7i4WJJUXFyswYMHO+FFkgoKChSNRrVp06Ym11NdXa1oNBo3AQCAk1ObBphYLKbJkyfrwgsv1KBBgyRJ4XBYKSkp8vv9cbWBQEDhcNipOTy8NLQ3tDVl1qxZ8vl8zpSTk5PgrQEAAB1FmwaYiRMnauPGjXrmmWfacjWSpOnTpysSiTjTrl272nydAACgfSS31YInTZqkhQsXauXKlfrWt77lzA8Ggzp06JAqKyvjzsKUlZUpGAw6NatXr45bXsNdSg01R/J4PPJ4PAneCgAA0BEl/AyMMUaTJk3SggULtGzZMuXm5sa1Dxs2TJ06ddLSpUudeVu3btXOnTuVn58vScrPz9eGDRtUXl7u1CxevFher1cDBw5MdJcBAIBlEn4GZuLEifr73/+uf/zjH+ratatzzYrP51Nqaqp8Pp/GjRunKVOmKCMjQ16vV7fccovy8/N1/vnnS5JGjhypgQMH6oYbbtCcOXMUDod15513auLEiZxlAQAAib+N2uVyNTn/iSee0E9/+lNJ9Q+yu+222/T000+rurpaBQUFeuSRR+K+HtqxY4duvvlmLV++XF26dNHYsWM1e/ZsJSe3LnNxGzUAAPZp7fG7zZ8D014IMAAA2KfDPAcGAAAg0QgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWIcAAwAArEOAAQAA1iHAAAAA6xBgAACAdQgwAADAOgQYAABgHQIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKxDgAEAANYhwAAAAOsQYAAAgHUIMAAAwDoEGAAAYB0CDAAAsA4BBgAAWCe5vTtwqojFjPZsq9QX0Wp18XqU1c8vt9slEzOq3h5RbP8hubumyJPrk8vtau/utpoxdaqsXKPq6nJ5PJny+8+Ty5XU3t1qkamr04G1pardu1fJPXsqbfgwuZI6dp9PhLqY0ertFSrff1CZXTtrRG6GktrzdzFWJ+1YJVWVSekBqc8Fkpufk02a2+8BiUCAOQZN7uAVa3InWxer07o9a7V/TYliO7zataO3Dhz4elld/B59+8KgPBs+Uyx6yJnv9qbId1WuytO/UFVVldLT09WnTx+53R3vZFl5+T/1wbbfqbo67MzzeII6o99MZWYWtPn6D9XU6LUVL+lAxW6lZWRr5LevVkqnTi2+p/Kfi/TpPXfLvbfCmZccDCrw6+nyjhzZ4ntra2v13pLVipTvlS+zp84OjVBycsv/hepq6/RhyWbt3xdV125e9c0bqKTkYz8IJyoo1hmjtyurVH6oVpkpyTrfn64kl0uLNu7Rb1/erD2Rg05tlq+z7rpqoAoHZR3zeo7b5pekRVOl6O6v53mzpcL7pIFXn/j+WKYjhPSP3inXG89u0xeV1c68Ln6PLr6un04/N7NRfSxWp0+3bFJV5T6l+7up14Cz5P6GgbWjfTCMxWLasWNHh9+nt1ZH+eDqMsaYE77WVnr44Yd1//33KxwOa8iQIXrooYc0YsSIVr03Go3K5/MpEonI6/Ued1+a2sGPSV+vuzr9Valffn0AlzdbS0bcqFeXLNSo/61QzDNEG88aX9/m+vo/UFYnl85LS/pq9tfzt7vK9HbKNn3h+vo/vdfrVWFhoQYOHHjc25Eo5eX/1IaNEyUd+etTvy2DBz3cpiHmfxY8rgvenaVsfR1EditDq4ZM149+OKHJ97z51H8q4+4/H9bLekb1P4NeD/6h2RDzxjOvau1Lf1Wsbr8zz53UVcOvvlEXj7m8yfes/2eJFhe/ri/09e9MF3XW9/Iv1TkFea3c0sQFxf/dW6k7t32qPdU1zrwsTyf9SJ31/156v5mfpPToT4ae2BCz+SXpuRvV3O+Wrv0rIaYF0ddeU9m9s1Qb/vr3pbUhPVE+eqdcix7b2Gx74b8Pigsx20pWadn8x1VV8ZkzLz2jh7770wnql3fBMa37y42fqfLlj1QX+fqDYZIvRf6rTlfqoB7HtKxE2Lx5sxYtWqRoNOrM64j79NY6ER9cW3v87rAB5tlnn9WNN96oefPmKS8vT3/4wx/0/PPPa+vWrcrMbJzej5TIALNo4x7d/Ld1cbvTAvdqPdrpD5Kkw4P9krQ0PbMvQ1MWxGTkUvH5d6va448LL5L0va5Sqjs5Pry4y7W004b6F018WLj22ms7xC+8MXV6a9Ulcb/A8VzyeIK68IIVbZLK/2fB47pm/e2S4sc+9tUP6IVz7m8UYpZ8/Jo81/1C3fc3ObQykjoFg+q7dEmjT6pvPPOqVi94uNn+jPjhxEYhZv0/S/TiqlfrXxyZliSNuuDyVoWYRAXF/91bqf9v4/81XooxSlkRlqs61uT7XJKCvs56c+p3T8zXSbE66Q+D4s+8HNkjb7Y0eQNfJzUh+tpr+vQXk6Ujd+tf7WdaCumJEosZ/fXXq+LOvBwpvZtHN/z+ArndLm0rWaWXHri32dqrp/y61SHmy42f6fO/bWm2vftPBpzQELN582Y999xzzbZ3lH16a52oD66tPX532HNYDzzwgMaPH6+bbrpJAwcO1Lx585SWlqa//OUvJ7QfdTGj3768Oe7H5VZMd3X6a/2/D9un10m6r5tfY5fUHwwi/r6q7tytUXjpnmSUltQpLrzEZPR2pw/qXzRznFi0aJFisaYPNCdS/anD5sKLJBlVV+9RZeWahK/7UE2NLnh3lqT4sT/89QXvztahmq/PMtTF6vQ//3O3ejQTXqT6+bXhsA6sLY2bX1tbq7Uv/bXFPq196a+qra39en21dVpc/PrXCz5yRZIWF7+uutq6FpdrTJ0+2PY7Nd5ZyJn3wba7ZUzLy6kzRndu+7TJpbj2HWo2vDSsZU/koFZvr2i2JqF2rGohvHzVo+in9XWIY+rqVHbvrMbhRXLmld07S6au5d+X47VnW2WL4UWSqvZVa8+2SsVidVo2//EWa19/8nHFYkfvs4kZVb78UYs1lS9/LBM7MZ/ZY7GYFi1a1GJNR9mnt0ai9keJ1CEDzKFDh1RaWqpQKOTMc7vdCoVCKi4ubvI91dXVikajcVMirN5eEfe1kSSNcL+vbFdFowPous4eZexxOwfK6pSmk2OK2ddoXthdWf+1UQsfcqPRqHbs2HGsm5Bw1dXlCa07Fq+teEnZajz2DdwuKVuf67UVLznz1pWvkz5r3QG4du/euNfvLVkd97VRU2J1+/XektXO6w9LNtd/bdRCWvpCB/VhyeYWl5uooPh2ZVXc10Zxqlu3synff/DoRYlQVZbYulPIgbWlcV8bNWJMkyE90b6IthxeDq/7dMumuK+NmrL/88/06ZZNR11e9fZI3NdGTamLVKt6e6RV/TteO3bsOOpxqKPs01ujPT+4NqdDBpjPPvtMdXV1CgQCcfMDgYDCzfwHnTVrlnw+nzPl5OQkpC9N7bgzVdlk7d6kJHWr+vq151DTv7wH675oNO9Lte4/fVVV1dGL2pjHc/Sv8I6l7lgcqGjp03nTdXsP7NW+9NYtP7lnz7jXkfK9zVTGO7xu/77Wheej1SUqKJYfqm2+0dO6r2Eyu3ZuVd1xSw8cveZY6k4hR4bv4637prp4Pa2uq6ps/GGuKa2pi+1vObwca93xau2+uiPs01ujPT+4NqdDBphvYvr06YpEIs60a9euhCy3qR13ufxN1vasq4s7UPorP5Tn4L5Gp3Q/q5UO1EZ1+OVHqWrdf/r09FYeiduQ33+ePJ6gWjrF4PFkye8/L+HrTsvIPua6nmk9tSXHpc+6Ss2drI1JimVmKG34sLj5vsyeTb/hCIfXde3WumuujlaXqKCYmdL8nVKxbikyHneTJ4Wl+p9wlq/+jrsTos8F9de4tHT6yturvg5xjgzfx1v3TWX186uLv+X9WXq3+luq0/3dWrXM1tS5u6a0almtrTterd1Xd4R9emu05wfX5nTIANOjRw8lJSWprCz+NHFZWZmCwWCT7/F4PPJ6vXFTIozIzVCWr3Pc7nR17EztNhk68qvUoQerVZEVcw6ULhn1+/D5+sbDwoo7uZfWVbz11ez6+cGYX12Mp+mvF7/i9XrVp0+fBGzV8XG5knRGv5kNr45slSSd0W9Gm1zAO/LbV2u3Go99g5iRdqu7Rn7767tUhmYOVWZ6UE9+L0kuNQ4xsa963euOGY0u4D07NELupK4t9smd1FVnh76+O65v3kB1Uefmf5am/m6kvnktX7yXqKB4vj9dWZ5OTS/F5VLtAL9cTayl4fVdVw08cc+DcSfV3yod14MjelQ4mwt4m5A2fJiSg8FG19w5XC4lB4ONQnqiud0uXXxdvxZrLrq2n9xul3oNOEvpGS1fVNu1ew/1GnDWUdfryfUpyddyOEnyeeTJ9R11WYnQp0+fox6HOso+vTXa84NrczpkgElJSdGwYcO0dOlSZ14sFtPSpUuVn59/QvuS5HbprqvqDzQNP7aY3PptzY31/z7sIJUkaeq+Sj0ZcjsHyszP3tWgTX+Sp7rSqXO53Iqm99Vb5S/qy6+ur3DLpfNrzqgvaObGsMLCwg7z7IDMzAINHvSwPJ74U/keT7BNb6FO6dRJq4ZMl6RGIabh9aoh0+KeB5PkTtK0EdO0ur9bD1yTpIoj8khFV6lixjj5CwobrS85OVnDr76xxT4Nv/rGuOfBJCUn6Xv5l9a/OPJH+dXr7+VfetTnwSQqKCa5XLqnX69mlxILpGr81Wcq6Is/2xj0dT7xt1BL9bdIX/tXyXvEer3Z3ELdAldSkgK/nv7ViyN+0l+9Dvx6+gl5Hszp52aq8N8HNToTk97NE3cLtdudpO/+tOnHHjS4dOyEVj0PxuV2yX/V6S3W+K867YQ9D8btdquwsPE+5XAdaZ9+NO35wbXZPnXk26jHjh2rxx57TCNGjNAf/vAHPffcc3r//fcbXRvTlPZ7DkwvLRlxg/McmB5fXf9p5NLnfc6R99qb1OOi4crq59dHa4q1bP6flHqgs1KT0vVlXZX2ZbhUHcjRgYMd+zkwDdrrgUZNPwemu1YNmdbsc2CW7Fii2atnq7wqrAG7jLpVSa4eGRr9oxkKndbyraUd7zkwWTqj34zjfg5MtqeT7u7XS1f29PMk3pNER3gOTIPWPom3qefAdO3eQ5eOTdRzYDzyX3Uaz4FJgETtj1pi/XNgJOmPf/yj8yC7c845R3PnzlVeXut2/IkOMNI3fxJvty+kvqefp/TzRjT69NPU0ycl10n11Ma28k2exFsXq9O68nXae2Cveqb11NDMoUpq5UHxZH4SL04uHeFJvMeKJ/Hao60/uJ4UAeZ4tEWAAQAAbcv6B9kBAAA0hwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFin5eegW6zhAcOH//0JAADQsTUct4/2hwJO2gCzf3/9H93Lyclp554AAIBjtX//fvl8vmbbT9q/hRSLxbR792517dpVrqP8sbpoNKqcnBzt2rWLv5uUYIxt22Fs2w5j23YY27ZzsoytMUb79+9XdnZ2i3/08qQ9A+N2u/Wtb33rmN7j9Xqt/qF3ZIxt22Fs2w5j23YY27ZzMoxtS2deGnARLwAAsA4BBgAAWIcAI8nj8eiuu+6Sx+Np766cdBjbtsPYth3Gtu0wtm3nVBvbk/YiXgAAcPLiDAwAALAOAQYAAFiHAAMAAKxDgAEAANY55QPMww8/rH/5l39R586dlZeXp9WrV7d3lzq83/zmN3K5XHHTmWee6bQfPHhQEydOVPfu3ZWenq7Ro0errKwsbhk7d+7UlVdeqbS0NGVmZur2229XbW3tid6Udrdy5UpdddVVys7Olsvl0osvvhjXbozRzJkzlZWVpdTUVIVCIW3bti2upqKiQkVFRfJ6vfL7/Ro3bpyqqqriat577z1dfPHF6ty5s3JycjRnzpy23rR2d7Sx/elPf9ro97iwsDCuhrFt2qxZs3Teeeepa9euyszM1KhRo7R169a4mkTtB5YvX66hQ4fK4/Gob9++mj9/fltvXrtqzdh+5zvfafS7+7Of/Syu5pQYW3MKe+aZZ0xKSor5y1/+YjZt2mTGjx9v/H6/KSsra++udWh33XWXOeuss8yePXucae/evU77z372M5OTk2OWLl1q1q5da84//3xzwQUXOO21tbVm0KBBJhQKmXfeece88sorpkePHmb69OntsTnt6pVXXjF33HGHeeGFF4wks2DBgrj22bNnG5/PZ1588UXz7rvvmquvvtrk5uaaL7/80qkpLCw0Q4YMMW+//bZ54403TN++fc3111/vtEciERMIBExRUZHZuHGjefrpp01qaqp57LHHTtRmtoujje3YsWNNYWFh3O9xRUVFXA1j27SCggLzxBNPmI0bN5r169ebK664wvTu3dtUVVU5NYnYD3z88ccmLS3NTJkyxWzevNk89NBDJikpySxatOiEbu+J1Jqx/fa3v23Gjx8f97sbiUSc9lNlbE/pADNixAgzceJE53VdXZ3Jzs42s2bNasdedXx33XWXGTJkSJNtlZWVplOnTub555935m3ZssVIMsXFxcaY+gOL2+024XDYqXn00UeN1+s11dXVbdr3juzIg2wsFjPBYNDcf//9zrzKykrj8XjM008/bYwxZvPmzUaSWbNmjVPz6quvGpfLZT799FNjjDGPPPKI6datW9zYTp061fTv37+Nt6jjaC7A/OAHP2j2PYxt65WXlxtJZsWKFcaYxO0HfvWrX5mzzjorbl3XXXedKSgoaOtN6jCOHFtj6gPML37xi2bfc6qM7Sn7FdKhQ4dUWlqqUCjkzHO73QqFQiouLm7Hntlh27Ztys7O1mmnnaaioiLt3LlTklRaWqqampq4cT3zzDPVu3dvZ1yLi4s1ePBgBQIBp6agoEDRaFSbNm06sRvSgW3fvl3hcDhuLH0+n/Ly8uLG0u/3a/jw4U5NKBSS2+1WSUmJU3PJJZcoJSXFqSkoKNDWrVu1b9++E7Q1HdPy5cuVmZmp/v376+abb9bnn3/utDG2rReJRCRJGRkZkhK3HyguLo5bRkPNqbSPPnJsGzz11FPq0aOHBg0apOnTp+vAgQNO26kytiftH3M8ms8++0x1dXVxP2BJCgQCev/999upV3bIy8vT/Pnz1b9/f+3Zs0e//e1vdfHFF2vjxo0Kh8NKSUmR3++Pe08gEFA4HJYkhcPhJse9oQ31GsaiqbE6fCwzMzPj2pOTk5WRkRFXk5ub22gZDW3dunVrk/53dIWFhbrmmmuUm5urjz76SL/+9a91+eWXq7i4WElJSYxtK8ViMU2ePFkXXnihBg0aJEkJ2w80VxONRvXll18qNTW1LTapw2hqbCXpxz/+sfr06aPs7Gy99957mjp1qrZu3aoXXnhB0qkztqdsgME3d/nllzv/Pvvss5WXl6c+ffroueees+KXHpCkMWPGOP8ePHiwzj77bJ1++ulavny5LrvssnbsmV0mTpyojRs36s0332zvrpx0mhvbCRMmOP8ePHiwsrKydNlll+mjjz7S6aeffqK72W5O2a+QevTooaSkpEZXxZeVlSkYDLZTr+zk9/t1xhln6MMPP1QwGNShQ4dUWVkZV3P4uAaDwSbHvaEN9RrGoqXf0WAwqPLy8rj22tpaVVRUMN7H6LTTTlOPHj304YcfSmJsW2PSpElauHChXn/9dX3rW99y5idqP9BcjdfrPek/LDU3tk3Jy8uTpLjf3VNhbE/ZAJOSkqJhw4Zp6dKlzrxYLKalS5cqPz+/HXtmn6qqKn300UfKysrSsGHD1KlTp7hx3bp1q3bu3OmMa35+vjZs2BB3cFi8eLG8Xq8GDhx4wvvfUeXm5ioYDMaNZTQaVUlJSdxYVlZWqrS01KlZtmyZYrGYs1PLz8/XypUrVVNT49QsXrxY/fv3PyW+4mitTz75RJ9//rmysrIkMbYtMcZo0qRJWrBggZYtW9boa7RE7Qfy8/PjltFQczLvo482tk1Zv369JMX97p4SY9veVxG3p2eeecZ4PB4zf/58s3nzZjNhwgTj9/vjrtxGY7fddptZvny52b59u3nrrbdMKBQyPXr0MOXl5caY+tsne/fubZYtW2bWrl1r8vPzTX5+vvP+hlv8Ro4cadavX28WLVpkevbseUreRr1//37zzjvvmHfeecdIMg888IB55513zI4dO4wx9bdR+/1+849//MO899575gc/+EGTt1Gfe+65pqSkxLz55pumX79+cbf6VlZWmkAgYG644QazceNG88wzz5i0tLST/lbflsZ2//795pe//KUpLi4227dvN0uWLDFDhw41/fr1MwcPHnSWwdg27eabbzY+n88sX7487lbeAwcOODWJ2A803Op7++23my1btpiHH37Yult9j9XRxvbDDz80v/vd78zatWvN9u3bzT/+8Q9z2mmnmUsuucRZxqkytqd0gDHGmIceesj07t3bpKSkmBEjRpi33367vbvU4V133XUmKyvLpKSkmF69epnrrrvOfPjhh077l19+aX7+85+bbt26mbS0NPPDH/7Q7NmzJ24Z//d//2cuv/xyk5qaanr06GFuu+02U1NTc6I3pd29/vrrRlKjaezYscaY+lupZ8yYYQKBgPF4POayyy4zW7dujVvG559/bq6//nqTnp5uvF6vuemmm8z+/fvjat59911z0UUXGY/HY3r16mVmz559ojax3bQ0tgcOHDAjR440PXv2NJ06dTJ9+vQx48ePb/ThhbFtWlPjKsk88cQTTk2i9gOvv/66Oeecc0xKSoo57bTT4tZxMjra2O7cudNccsklJiMjw3g8HtO3b19z++23xz0HxphTY2xdxhhz4s73AAAAHL9T9hoYAABgLwIMAACwDgEGAABYhwADAACsQ4ABAADWIcAAAADrEGAAAIB1CDAAAMA6BBgAAGAdAgwAALAOAQYAAFiHAAMAAKzz/wMoMku+yXqfiQAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1552 1154 0.0\n",
      "1552 is in county 85\n",
      "its neighbor units are [1561, 1551, 2338, 1713, 1714]\n"
     ]
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.5:\n",
    "        plt.scatter(u, unitPop[u])\n",
    "plt.show()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < 0.5 and unitPop[u] > 5:\n",
    "        print(u,unitPop[u], unitUse[u])\n",
    "        for c in range(nCounties):\n",
    "            if u in countyUnitList[c]:\n",
    "                print(u,\"is in county\",c)\n",
    "                print(\"its neighbor units are\",unitNbrs[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "ce9292b0-7d6a-419a-9491-d0def779ad04",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are a total of 4106 populated HDs\n"
     ]
    }
   ],
   "source": [
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if len(HDunitList[t]) > 0:\n",
    "        popHDlist.append(t)\n",
    "populatedTractList = popHDlist.copy()\n",
    "print(\"there are a total of\",len(populatedTractList),\"populated HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 181,
   "id": "f7f36559-7f1d-4203-8b24-0e8cc2ce1753",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this will show if we had any duplicated units in HDunitLists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this will show if we had any duplicated units in HDunitLists\")\n",
    "excess = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    excess[t] = len(HDunitList[t]) - len(set(HDunitList[t]))\n",
    "plt.hist(excess)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "27bc7f0a-d7ff-4c68-830f-29ba5013c314",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#popHDlist = populatedTractList.copy()  #somehow our popHDlist started to include the cut District HD starters\n",
    "HDunitList = [list(set(HDunitList[t])) for t in range(nHDs)]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t]]) for t in range(nHDs)]\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "id": "af8a4945-40c2-40df-8dd4-d516f4de2f0f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 701 time is now 95\n",
      "working on HD 1401 time is now 189\n",
      "working on HD 2103 time is now 284\n",
      "working on HD 2803 time is now 392\n",
      "working on HD 3503 time is now 479\n",
      "out of 4106 total HDs, there were 1900.0 contiguous and 34.0 complement-contiguous HDs\n",
      "2189 HDs had both discontiguity problems, while enclave-only = 1883 and discontig only= 17\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 2206 1883\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"FIND DISCO\" CODE\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%700 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs,4) #,6) #6 is high (slow) to try to avoid false enclaves\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 184,
   "id": "40f06e44-45be-4a36-b62c-26698af70e06",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 677646 district pop vs 713311 target\n",
      "we'll also trim any HD with total islands' pop <= 14266\n",
      "working on HD 0\n",
      "working on HD 296\n",
      "working on HD 697\n",
      "working on HD 1036\n",
      "working on HD 1366\n",
      "working on HD 1694\n",
      "working on HD 2095\n",
      "working on HD 2418\n",
      "working on HD 2716\n",
      "working on HD 3169\n",
      "working on HD 3802\n",
      "working on HD 4103\n",
      "Out of 2206 discontig HDs 2206 had discontig HDs.\n",
      "Of these, 2134 won't be under 677646 after all minor discontigys were shed, while 72 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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Cu2A/l4tbVqUgZk3XgWIAVccYQBERUX1hkwR+vyAJxbkmOVg6J4VgWtGLWOi1FGHqTBQJNbxUEoQAbCgZacpEC7l9kShJfr4BLQZYP8BFESxfP8DXCwCQe8P9quJV/XkaciVyBlAVYABFRET1wZaUS3hxzSH5eekRJ7sMqSVy4QsdriPe+mdcRYA8wmRvb4Ev/mZ9AifQDkYEI27wnQhursXZqzfw0bZfHRLCq3NarTZxKxciIqImLv67o/ji5/OKY0YEYVrRi/hGmyAfm1I0CadEa/ghHyYEObQfbo1zyHcKbq7Foz1Ccf/7O8otbqlCSXHLhyP08FCranTkqCFhAEVERFRP3T8/CRfMVofjBmRhoddSxbGFXkvlnChnygZVQEm5AHeKW5rzrQ1+D7vqwjIGRERE9Uy+1YaOb2wuN3gqnQP1RGECzkkhCFNnYp1mHgzIcuk97OUCXC1amZRmahR72FUXBlBERET1yPh/7cOdcxJRLDme05cJnkZY43BQdJZrOtmDKL0LQZS9TpOrRSs3HL7UKPawqy5uBVA2mw1xcXEIDw+Hj48POnTogHnz5qF0Hvqzzz4LlUqleAwcOFBxnezsbIwaNQr+/v4ICAjAuHHjcO2acnfolJQUPPDAA/D29kabNm2wYMECh/6sX78eXbt2hbe3NyIjI7FlyxbFeSEE5syZA4PBAB8fH8TExODUqVPu/MhERES1wlosYcDfdiIpzbGCuN11+CAL/ooSBsCtCuTnpBBkwR/X4VPuNVr4emF5qaRwV4pbBvp5Ifu642iYXXmbBzdmbuVAvf/++1i2bBm++OILdOvWDfv378dzzz0HnU6Hl19+WW43cOBAfP755/JzrVaruM6oUaNgNBqRlJSEoqIiPPfcc5gwYQLWrFkDoCR7fsCAAYiJicHy5ctx9OhRjB07FgEBAZgwYQIA4Oeff8bIkSMxf/58PProo1izZg2GDh2KgwcPonv37gCABQsWYNGiRfjiiy8QHh6OuLg4xMbGIi0tDd7e9b9MPBERNX42SeDFVQewNe1ypW3z4Isx1pluJYoDwNCeoWjdwhfRHYLQt32QIunbXlV84qqDUMF5ccvHe96Bz3afrbR/DWEPu+riVhmDRx99FK1atcJnn30mHxs2bBh8fHywatUqACUjULm5udiwYYPTaxw/fhwRERHYt28f+vTpAwBITEzEoEGDcOHCBYSGhmLZsmV48803YTKZoNFoAAAzZ87Ehg0bcOLECQDA8OHDcf36dWzatEm+dt++fdGzZ08sX74cQgiEhobilVdewauvvgoAMJvNaNWqFVauXIkRI0ZU+vOyjAEREdWksuUJaoJB541dMx66reKWOh8NRn76S6XvtXZ8X0R3cJ7EXptq4/vbrSm8e++9F9u3b8evv/4KADhy5Ah27dqFRx55RNFu586dCAkJQZcuXTBx4kRkZd2ai01OTkZAQIAcPAFATEwM1Go19uzZI7fp16+fHDwBQGxsLE6ePImcnBy5TUxMjOJ9Y2NjkZycDABIT0+HyWRStNHpdIiKipLblFVYWAiLxaJ4EBER1YR5m9JqPHgCnO9J58zA7gbsmvEQ1o7vi49H9MTa8X2xa8ZDGNjd0Kj2sKsubk3hzZw5ExaLBV27doWHhwdsNhveeecdjBp1a9PCgQMH4oknnkB4eDjOnDmDN954A4888giSk5Ph4eEBk8mEkJAQZSc8PREYGAiTyQQAMJlMCA8PV7Rp1aqVfK5FixYwmUzysdJtSl+j9OuctSlr/vz5mDt3rju3hIiIyG3Pfb4XP5y8UqPv0cLXC/OfiHSrvICHWuV0BMmVaT5XA7XGwq0A6uuvv8bq1auxZs0adOvWDYcPH8bUqVMRGhqKMWPGAIBiaiwyMhI9evRAhw4dsHPnTvTv3796e1/NZs2ahenTp8vPLRYL2rRpU4c9IiKixuaB97chI6ewWq8Z4OOFT0b0wp6zWQBUTnOdbtfA7gYsG93bYZpP30TrQLkVQL322muYOXOmHCRFRkbi3LlzmD9/vhxAldW+fXsEBwfj9OnT6N+/P/R6PTIzlSsMiouLkZ2dDb1eDwDQ6/W4fFmZTGd/Xlmb0uftxwwGg6JNz549nfZVq9U6JLwTERFVB2uxhAfe34bLeUWVN3bTc/e1wwNdWuLeTsFylfC96dnVXiV8YHcDHo7QsxI53Aygbty4AbVamTbl4eEBSXJSrOKmCxcuICsrSw5ioqOjkZubiwMHDuDuu+8GAOzYsQOSJCEqKkpu8+abb6KoqAheXiWbGyYlJaFLly5o0aKF3Gb79u2YOnWq/F5JSUmIjo4GAISHh0Ov12P79u1ywGSxWLBnzx5MnDjRnR+biIjotryzOQ2f/i+9Rq7dwtcLkx/q5DQJPMDHC2PubYd7wgNx9VphtQQ85U3zNTVurcJ79tlnsW3bNvz9739Ht27dcOjQIUyYMAFjx47F+++/j2vXrmHu3LkYNmwY9Ho9zpw5g9dffx15eXk4evSoPLrzyCOP4PLly1i+fLlcxqBPnz5yGQOz2YwuXbpgwIABmDFjBlJTUzF27FgsXLhQUcbgwQcfxHvvvYfBgwdj3bp1ePfddxVlDN5//3289957ijIGKSkpLpcx4Co8IiK6Xc/9cy9++LXm8p2Wj+4NAJi46qDTQpdlNYWtV2rj+9utACovLw9xcXH4z3/+g8zMTISGhmLkyJGYM2cONBoN8vPzMXToUBw6dAi5ubkIDQ3FgAEDMG/ePEUyd3Z2NiZPnoyNGzdCrVZj2LBhWLRoEZo1aya3SUlJwaRJk7Bv3z4EBwfjpZdewowZMxT9Wb9+PWbPno2zZ8+iU6dOWLBgAQYNGiSfF0IgPj4eK1asQG5uLu6//34sXboUnTt3dunnZQBFRES344H3tyMjp2ZqI6lVwOKRvRHbXY/7399R4X52pdnHnpaVKqbZ2NS7AKqpYQBFRERVYZMEoucnIbMa8p3KrnqzW/p0LwzqEYrkM1ku1Wgqe029i/WhGqJ6VweKiIiIymctljD9q0Po+MaW2w6evhx7D5aP7g29TplyYtB5Y/no3hjUIxRA1ap/N8WtV6qbW0nkRERE5ESBGYu+P4i/7bnhcEqPLKfbq1TEoPPGvR2D4aFWVbrqzdXNgJ1pSluvVDcGUERERLfBdiMXp/42AI9Zc7AWtzb4BQADsrBOMw9Z8McY60yXg6i4wbeKUla26s1eJdzVHKjSbif4auo4hUdERFRFialGPDDvO/hYcxCmzsQ6zTwYULJ9mT14ClNnIggW+CHf5eu28NNU3ugme5VwdzKZmuLWK9WNARQREVEVbNifgRdWHcQlEYQR1jick0LkIKq36lc5eDonhWCENQ4muF47yd2pNXuV8ABfr0rbNtWtV6obV+FVgKvwiIioLJskEPPhTqRnKfOdSo842dmDJ6MbwRMArB3ft0rFKm2SwOIdp/D57rPIzXeexM46UNWDAVQFGEAREVFpmw5fxEvrDpdbsLK36ld8o02Qnz9RmICDwrXag3YBvl44MPvh2xodsklCTjwP9tMCKlRbJfKGoDa+v5lETkREVJECM1B4DeO/vYSkNOVerqVX2BmQhYVeSxXnF3otdXsE6rl7w+UAp3Qg5E7ww+1Wah4DKCIiovIUmCG+HIarmReRmjcLKGeF3evWCfhM81c552la0YtY6LVUzolyNYgK8PXC5Ic6AoDTve2awvRbQ8EkciIionL8kPIbLl48j5ZFl8pdYReCXKzUvK9IGD8oOjsklutvvrYi7z0RCQ+1CompRkxcddChNIHJXICJqw4iMdXo8s9gkwSSz2Th28MXkXwmCzaJmTvVgSNQREREZRWYkbjvV7ywORMGzJaDpXWaeXi7aBTivL5EW/VVnJNCMM76KhZoVsAmeShGmowoWZ1nH6W6Dp9y3670yJJNEpi7Mc1pnpVAySq6uRvT8HCEvtLpPI5i1RwmkVeASeRERE2P7UYuTvz1YTQrzpUDImcr7M5LwRhujYcRQWiOG/BDvtNSBWUrkdtDnqkxndEu2Ncht8nVve3Wju+Le8IDy82Rso9ilf2S52bC1YMjUERERDdtOnwJb6/bhq80uQ75S28XjcKn2oVy23lFz8ijTXnwdagy7qEChva6A7tOaZGXVygf11cyAuRqDahtaSZM//qw09GlhyP01TaKRc5xBKoCHIEiImo6xv9rn7zKrvSI0zkpBO8UjcISzcfwUklye1drPOn9tRh5T1u0C/ZzaSWdqyNQztwa3eqEhdtOVdq+qvWm6rva+P5mEjkRETV58RuOKkoU2POX7EngK7QL4aWSUCTUGF84TZEcbqgkOfyypRAfbTsFraca0R2CKh3xse9tV14rFYDyLmEfEfl899kK38OOmwlXHQMoIiJqsqzFEvq+m4QvfjnvcM4+bVfaJOsUJInfubXCzh7UzN2Y5tIKOPvedgAcgijVzetVdBkBlFuFvCxuJlx1DKCIiKhJenvjMXSe/T1MFqvT8wZkYY7XKsWxN71Ww4AsxQhVZSvsgJKgxmguwN70bJf6Zt/bTq9TBjh6nTfG3tfOpWsE+HhVOIrFzYRvD5PIiYioyRn88Y84ZrxW7nl7DlQb9RVkSC3xVtFozPZa7ZBYPtwap1hhVxl3pswGdjfg4Qi9wyq7venZ+KcLU3TP3ReOj7b9Ko9a2XEz4erBAIqIiJoMmyTQ662tsBTYym2jL5NAbg+WUq3tFfWghlvjnJYtqIi7U2bOtmSx50iZzAVOV9mpUDJSNfmhjuiib+ZQB6qyVYDkGgZQRETUJCSmGvHi6oMV5g8BwHX4IAv+gIQqF8Ysyx7UVMeUmT1HauKqg5WOLpU3isWRp9vHMgYVYBkDIqLG4dtDFzHlq8Mut3enMCYARSBTXlBT3YUrWWW8fLXx/c0AqgIMoIiIGjZrsYRBH/2I01dv1Oj72AMXALUa1NgkwdElJ1iJnIiIqIrmb0nD339Kr7Hrxw2+E8HNtQ6BS21OmTnLkaLawQCKiIgahwIzYDHC6umHUV+fx76zufIpPbLgh3xkItDlFXMVMei88ex94U4DIwY1TQMDKCIiavgKzMA/B6E48wQyJR0uWBOAm/lLBmRhg2Y2AlTXcFy0xTPWN287iBrxu7a332dq0FhIk4iIGr4rpyBlpsITxWitzsJ6TQIMyJKDp1ZqM7QqG1ohB37Id/myzb2djzMs3PYr7n9/BxJTjdX1E1ADwwCKiIgavOe/3A9J3PpKa63Own80c7BJ+wZaqc0AACGAN6zj3KrdNHdIN0yL6eT0nMlcgImrDjKIaqIYQBERUcNTYAYyT8CanYG75m7FNksbDCtMQHGpIEqvzkGQKg9ASfD0fOEr+AF3u/U2rXTeWLcvw+k5d/e4o8aFARQRETUsBWbgX0NRvOx+ZH70IHzzLwMAjqAj/lI4Dc6K88y0Po/tbgZPBp03IKAoSVCWu3vcUePBAIqIiBqGAjNgvggUXkOmKQOeokjOd+qB0+iIC3hb80+onFQMeMnrPzAgy623ix8SgavXC11q684ed9Q4MIAiIqL6r8AMrBoGsXIQnlz6Pzx2Yw4uSMEASvKdvtHGY4t2JgzqHKcvL51YXhm1Clj6dC8M7G5wee86d/e4o4aPARQREdV/hddwPdsEVc5ZfJgfBwB4yhoPo9QCAOCpEtCoJLm5EMB71uGKnCh7EKWvJIhaPLI3BvUIBXBr497yymCqUDLVVx173FHDwgCKiIjqr5vTdo+uPI2Y7NdxTgpBmDoT6zTz0F31G9RwTHiyJ4wvlx5TJJYLAVyHttxNgAN8vbB8dG8M6nFryxX7xr0AHIKoshv3UtPCAIqIiOqny2nAPwfiwsI/IMt4DkYEYYQ1Tg6iPtUuRCt1rsPLrormSEM7ACWJ5fYgKh8aTLJOKbeI5pKRzjf7HdjdgGWje0OvU07T6XXe1b5BMDUc3Ey4AtxMmIioDhSYgSunIL54FCjKh0oFnJNCMMIaBwHgSdUPeFX7jeIlJqkF1CoJIaqSmk8XpCA8ZU2A8WbNp0icxlUEwIhgh7dToSQY2jXjoQpHkrhxb8NRG9/fDKAqwACKiKiW3UwWN5vS4VeUDU+VBCEAlQq4IAXDFzfQQnVDsdKuSKjwZOFcZKIF1mvmorX6KoCSIOpJa0KFhTPtl+FIUuNSG9/fnMIjIqK6l5sB/PYjcPU0jJcyoCu+iivCH8VCDZWqJH+ptfoqAtU35OdFQoUioYKXSmCRZjGAksTyC1IwCoUnrsK/3HwnO07DUVVxBKoCHIEiIqoFuRnAknuAohu4qgrEuPypWKRZjDB1Jq5IzRCsuuZQ2+mvhcOQKKLgiwJ8crPtOSkEw60lK/T8kI9MBDrkO/lpPDD+gfYIb+nHabhGrDa+v53vkkhERFRbrmUCtpKClcEiG8s1C/GCdRqWa/4Gg5MkcQB4yut/+Lf19ziN1hhhjcM6zTxk3RxxKi9JfEr/jni5f2cGTFQtOAJVAY5AERHVkAIzUHgNVj8DVu5Kx6HkJHxSMAueN2s5ZYtm0OE6PFTOyxSUTiw3Igh6ZJUbPBl03ogfEsFpuiak3uVA2Ww2xMXFITw8HD4+PujQoQPmzZuH0jGYEAJz5syBwWCAj48PYmJicOrUKcV1srOzMWrUKPj7+yMgIADjxo3DtWvXFG1SUlLwwAMPwNvbG23atMGCBQsc+rN+/Xp07doV3t7eiIyMxJYtWxTnXekLERHVstwMYOUQZC+NwYOzV+HdxBP43qzcDDhQdc0heMqR/BQ5UfZ6UHpkwYQgOXgy6LwxLaYzPh7RE2vH98WuGQ8xeKJq51YA9f7772PZsmVYvHgxjh8/jvfffx8LFizAJ598IrdZsGABFi1ahOXLl2PPnj3w8/NDbGwsCgpu7RM0atQoHDt2DElJSdi0aRN++uknTJgwQT5vsVgwYMAAhIWF4cCBA/jggw+QkJCAFStWyG1+/vlnjBw5EuPGjcOhQ4cwdOhQDB06FKmpqW71hYiIalGBGWLdKBSbUhFYeAnrNPPKbK8iObxECOCy5I8W6usOieX50OA6fBDo54WFw28FTFNiOuGxnncgukMQp+yoRrg1hffoo4+iVatW+Oyzz+Rjw4YNg4+PD1atWgUhBEJDQ/HKK6/g1VdfBQCYzWa0atUKK1euxIgRI3D8+HFERERg37596NOnDwAgMTERgwYNwoULFxAaGoply5bhzTffhMlkgkajAQDMnDkTGzZswIkTJwAAw4cPx/Xr17Fp0ya5L3379kXPnj2xfPlyl/pSGU7hERFVrx/2HkKHzX9CW1UmioQaXioJ56QQvF00Cks1C+HlJNbJlvzwnHWGnFhulALQUmVBITzxWOE8nEYbLOdKOiql3k3h3Xvvvdi+fTt+/fVXAMCRI0ewa9cuPPLIIwCA9PR0mEwmxMTEyK/R6XSIiopCcnIyACA5ORkBAQFy8AQAMTExUKvV2LNnj9ymX79+cvAEALGxsTh58iRycnLkNqXfx97G/j6u9KWswsJCWCwWxYOIiKrHxiOX8Nw3lzC8sKSauJdKQpFQy1XFSwdPxUIFmyg5EKi+juWahXjZOhnnpBAYEYzRhTMRU/hX/KZqg6VPV1/wZJMEks9k4dvDF5F8Jgs2iWnC5Jxbq/BmzpwJi8WCrl27wsPDAzabDe+88w5GjRoFADCZTACAVq1aKV7XqlUr+ZzJZEJISIiyE56eCAwMVLQJDw93uIb9XIsWLWAymSp9n8r6Utb8+fMxd+5cF+4EERG5ylosYeTyXThwIQ8A5C1Z1mnmIUyd6dDeJOkwwfoKVAD+rU2Ap0qCQZ2D5ZqFmGCdhrMIlfOdlo7spdi77nYkphoxd2MajOZbaR5MQKfyuDUC9fXXX2P16tVYs2YNDh48iC+++AJ//etf8cUXX9RU/2rVrFmzYDab5UdGRkZdd4mIqEF7Z/MxdJ79vRw82RkRhHeKRjm0LxYq/MX6ClLQUbGPnSSAq9DJwZNB531z49/QaulnYqoRE1cdVARPAGAyF2DiqoNITDVWy/tQ4+HWCNRrr72GmTNnyvlDkZGROHfuHObPn48xY8ZAr9cDAC5fvgyD4Va0fvnyZfTs2RMAoNfrkZmp/D+O4uJiZGdny6/X6/W4fPmyoo39eWVtSp+vrC9labVaaLVa124GERGVr8CM19fsxte/Ok6B6ZGFcBixRPOx4niRgFxV3F6e4Ag64vHCBKgh8BvuQHREOJ67L7xaC2DaJIG5G9PgbLJOoGS7l7kb0/BwhJ4J6SRzawTqxo0bUKuVL/Hw8IAklayaCA8Ph16vx/bt2+XzFosFe/bsQXR0NAAgOjoaubm5OHDggNxmx44dkCQJUVFRcpuffvoJRUVFcpukpCR06dIFLVq0kNuUfh97G/v7uNIXIiKqZgVmIPMEsv8+BJPOTlGssNMjCx1xAf/RxGGN9l05B2pC4bSbOVGQc6Ls5QkA4Cg64gg6IQ++GBPdrkor6yrKbdqbnu0w8lSaAGA0F2BverZ794IaNbdGoIYMGYJ33nkHbdu2Rbdu3XDo0CH87W9/w9ixYwEAKpUKU6dOxdtvv41OnTohPDwccXFxCA0NxdChQwEAd955JwYOHIjx48dj+fLlKCoqwuTJkzFixAiEhpYMxT799NOYO3cuxo0bhxkzZiA1NRUff/wxFi5cKPdlypQpePDBB/Hhhx9i8ODBWLduHfbv3y+XOnClL0REVI1yMyCtG4VrOZeRX1CMMPVVrNPMwwhrHFoiB8s0CxGsskCrsgEAioUaTxYm4Ag64qi1vZwTVSTUsMDXYR+7AF8v9O1Q/sbA5akstykzz7XSNq62o6bBrTIGeXl5iIuLw3/+8x9kZmYiNDQUI0eOxJw5c+QVc0IIxMfHY8WKFcjNzcX999+PpUuXonPnzvJ1srOzMXnyZGzcuBFqtRrDhg3DokWL0KxZM7lNSkoKJk2ahH379iE4OBgvvfQSZsyYoejP+vXrMXv2bJw9exadOnXCggULMGjQIPm8K32pCMsYEBG5qMCMSx/HoOWN0/BSSbggBQFQobX6KoxSC7RUmeUq44XCE1nCHy9YpyIFHeVLGJCFdZp5sMAXE6zTYUSw4i2qUqrAnttU9ovOPn61bHRv6Hw0GPnpL5Vea+34voiuQgBHta82vr+5lUsFGEAREVXOJgn0j1+NL1Rz5REkexClURUjRGWW2xqlFnjGOgvX4AMTHIORpzoBB03FOJN3a4JE769Fwh+7uR082SSB+9/fUe70nAqAXueNH1/7Ax784AeYzAVO86Ds7XbNeIg5UA0ENxMmIqJ6beORS3hp7SEALTACcYppuNbqLIf2k4qm4DRaOxz3UAGfjOyFQT1CYZME9qZnIzOvACHNvaucMO5qbtOBczmIHxKBiasOQnXzuJ39XeOHRDB4IgW3ksiJiIjsieKv/mPzzeCphBFBeMk6GZekQHipHLdkAYCFXkvLbN1SYuYjXeWSBB5qFaI7BN32Vizu5DYN7G7AstG9odd5K87pdd5Yxirn5ARHoIiIyHUFZuBfQ2G9dBRTJX/sRgKMN6fiDMjCUs0iBJeasrMzSS1QDA95hZ29TAEAqFXAmHvDHV5zu0Kae1feqFS7gd0NeDhCXy2jX9T4cQSKiIgqV2AGzBdhvWHBxYvnoUERWquzsF6TgB44jY64gPWauWitvgrNzVV2dsVCDb06B4DABSnYoUzB+AfCofGs/q+je8IDYdB5o7zwR4WS1Xj3hAfKx6pr9IsaPwZQRERUsQIzxJfDcOWT/nhwwQ94sjAeF6SSFXKt1Vn4RhuPLdpZaK2+Kr9ECCBT0uGCFAzPm/WeSnKiSoKoLPgjX+WDv/QLx6xBETXSbQ+1CvFDSq5dNgxibhPdLq7CqwBX4RERAT/sPYT2m/+EMFUmzkkhGGGNAwB8o5kDgzrHoX2xUOOZwplIhwEqQE4st8EDOc06YU3r2Qho1RYjHoiskZGnsrjHXdPDMgZ1jAEUETV1ialGvLDqoFyjKUxdEkRNK3oRS70+vjk1d8tlEYDxhdMd6jt9pX0bbQx6qEasBgLa1PaPUW0r+6hhYBkDIiKqM9ZiCS+uPgigZIXdCOutMgXfaBOcvkYSwBW0UBwzIghnBn+Ftj3aA966mu62U/bcJqLqwhwoIiJykJhqRMScRJTaMg5GBGFa0YsObU1SC5hESdBkUOdivSZBLlUQ4OuF5aN74w/39Kqz4ImoJjCAIiIiBfu0XbGkzPAwIAuLvD5RHCsSKvzFOg2PF76lSCxfr0mAHllYMpI1lKhxYgBFRESwSQI/HLuMQR/9iBdXHXQ4b8+Baq3OQqHwhFV4oEio4KUSWKRZDAB4ylqyOq9QeOIq/NHMP6BKm/8SNQTMgSIiauI2Hb6IyesOl3teXyaBfJz1VQCALwrwiWaxXNdpuDUOT1rj0Qz5yEQgFvzpd0zUpkaLARQRURM2asXP2P2bYymC0q7DB1nwByQoKogDkBPLs+CP6/BBHnxh0HljAUsEUCPHMgYVYBkDImqUCsxA4TW0m3/Y4ZQeWXIgVFpz3IAf8mGC45TcP4eGopkuAMZCDUsEUL3AMgZERFS9CsyQvhyGjIxzMEA5mmTPc8qCP8ZYZyqCqDz4OgRVALD6+Sjc1zG4VrpOVJ8wiZyIqAlZuPkgMjLOyXlL9nIDpQtlBsECP+RXei2Dzht92zNJnJomBlBERE3Efe9tw8f7bmCENQ7npBA5iOqt+lWRJD7CGud0qq40FbiPHDVtzIGqAHOgiKgxyLfacOecRMWx0iNOdvbgyVhJ8NTC1wvzn4hkkjjVW8yBIiKiqrmZKP7MV+n4329mxSk9snANPphW9KJiS5ZpRS9WGjwN6aHHRyN6c+SJmjwGUEREjU2BGeLLYTifcQ6nrXGAk0RxC3wQgBuKly30WlruCFQzrQcWDOuBQT1Ca7r3RA0Cc6CIiBqZbYdO43wlieJdVRloo76Cc1IInihMUORE2dvbDet1B47ExzJ4IiqFARQRUSMy6h8/4/lvTRUmihcJNbxUkpzzdFB0dmivvxlENdN6YMFTd3HKjqgMBlBERI2ATRIIn7kZu0+XVBU3IkgRFH2jTUCYOhPnpWCcEG0dEsZLt7dXFQeABcN6MHgicoI5UEREDVxiqhEvONkA2Iggh0TxqUWTcUq0dlpV3IggDLfGyZXIn7+vXYOctrNJAnvTs5GZV8DK6FRjGEARETVg/zlwAdPWH3F6zoAsLPRaqjhWUaI4ADmo6t+1JWYP6Va9na0FialGzN2YBqO5QD5m0HkjnnvzUTXjFB4RUQNkkwR+/8GOCoOn0sUxK0sUL613Wx0+e/aemup6pWySQPKZLHx7+CKSz2TBJrlWrjAx1YiJqw4qgicAMJkLMHHVQSSmGmuiu9REsZBmBVhIk4jqnQIzkg6fwfgNjsGAfSNgP+TjqzKVxY0IcgiqhjupOB7g44kDcQPqbMqrqiNINkng/vd3OARPdioAep03ds14iNN5TUBtfH9zBIqIqKHIzcDZvz2EzluGO4wg9cBprNe8hS8070EFgSz4u5woXtp7dZg0fjsjSHvTs8sNngBAADCaC7A3Pbu6uktNHHOgiIgaANuNXPz60aPoKM7DSy1hnWaeHBzdhdP4P20CvFQSIAECKoyxznQpUdyurvOEbJLA3I1pcDYlIlAygjR3YxoejtA7DfAy88oPnqrSjqgyDKCIiOq5LSlGvLUmCV9pbsBLLaFIqOVcpneKRmGJ5mN4qUqOT7K+JAdNpQOk0n7Xoxs+/FMvHDiXU29WqrkzghTdwTEBPqS5t0vv42o7osowgCIiqsfe2ZyGT/+XDtycfitdDDNMnYkV2oUAgCKhxpOFCUhBxwqv92gPAz55ujcAOA1E6srtjiDdEx4Ig84bJnOB01Esew7UPeGBVe8kUSnMgSIiqofyrTYM+HDHzeCpROkcJi+VpGg/yToFRyoJngDg4YhW1d7X6nC7I0geahXih0QAKAmWSrM/jx8SwQRyqjYMoIiI6plnP9+DO+ck4tcr+Q7njAjC20WjHI6/6bW6wtIEdvV1Css+glReeKNCSZ5WRSNIA7sbsGx0b+h1yp9Rr/PGstG9WQeKqhWn8IiI6pFuc7bgurX86jJ34TSWaj5WHCudE1VRkUy9v7beTmHZR5CcVVR3ZwRpYHcDHo7QsxI51TiOQBER1QM2SaDTG5srDJ56lFptVyTUGF84TZ7OKx1E6csZiUr4Y7d6H0gE+Ho5HNP5erk1guShViG6QxAe63kHojsE1fufmRomBlBERHUsMdWIDm9sQZFUfhs9srBYs0gOlp4sTECS+J0iJ6pIqGGBr0N9J1+NB5bX8yksew2o3BtFDufMTo4R1TUGUEREdWhLyiWn01ZlXYcPriIA56VgDCtMkBPGSyeWnxBtMcE6XS5f4O2pxpT+nXA0IbZeB08V1YCym7sxzeUtXYhqA3OgiIjqgE0S+PC/J7B0528utc+Dr8vFMX01HvhLv/aY/FCnBjF9dbs1oIjqAgMoIqJatvHIJby89lCFIy7O5MHXaXFMH08VenXthg4t/RDdPhh9G1jeD6uIU0PEAIqIqBY9/8U+bDueWa3XXD6qD+7v0rJBBU2lsYo4NURu5UC1a9cOKpXK4TFp0iQAwO9//3uHcy+88ILiGufPn8fgwYPh6+uLkJAQvPbaayguLla02blzJ3r37g2tVouOHTti5cqVDn1ZsmQJ2rVrB29vb0RFRWHv3r2K8wUFBZg0aRKCgoLQrFkzDBs2DJcvX3bnxyUiqh65GbBl7McfP/7BIXiKxGkYcPW2Lj/mi324//0dFW62W1/YJIHkM1n49vBFJJ/Jgk0S1VIDiqi2uTUCtW/fPthsNvl5amoqHn74YTz11FPysfHjx+Ott96Sn/v63hputtlsGDx4MPR6PX7++WcYjUb8+c9/hpeXF959910AQHp6OgYPHowXXngBq1evxvbt2/H888/DYDAgNjYWAPDVV19h+vTpWL58OaKiovDRRx8hNjYWJ0+eREhICABg2rRp2Lx5M9avXw+dTofJkyfjiSeewO7du6twm4iIqig3A8Wf3ANRXABVYQJQqlq4fRPgQnjh4cIPYERwld/GZC7AxFUH63XByMRUI+ZuTFPkO9k3MY4fEoGJqw5CBSimNllFnOorlRCiyssapk6dik2bNuHUqVNQqVT4/e9/j549e+Kjjz5y2v7777/Ho48+ikuXLqFVq5LtBJYvX44ZM2bgypUr0Gg0mDFjBjZv3ozU1FT5dSNGjEBubi4SExMBAFFRUfjd736HxYsXAwAkSUKbNm3w0ksvYebMmTCbzWjZsiXWrFmDJ598EgBw4sQJ3HnnnUhOTkbfvn1d+vksFgt0Oh3MZjP8/f2repuIqCkqMAOF1/CP73/GmOMTFOUHLqMFwmHEv7TvycefKEzAURe2YqmIfb+3XTMeqnfBhr1MQdkvHHsvl40u2Z+vvACrvgaFVD/Vxvd3lcsYWK1WrFq1CmPHjoVKdesPdfXq1QgODkb37t0xa9Ys3LhxQz6XnJyMyMhIOXgCgNjYWFgsFhw7dkxuExMTo3iv2NhYJCcny+974MABRRu1Wo2YmBi5zYEDB1BUVKRo07VrV7Rt21Zu40xhYSEsFoviQUTkttwMiJVDYPz4IXx2OB9PFiagSKjhpZLwf9o52KKdhdXadxVB1e0GT4BytVp9UlGZAvuxuRvT8HCEHrtmPIS14/vi4xE9sXZ8X+ya8RCDJ6qXqhxAbdiwAbm5uXj22WflY08//TRWrVqFH374AbNmzcKXX36J0aNHy+dNJpMieAIgPzeZTBW2sVgsyM/Px9WrV2Gz2Zy2KX0NjUaDgICActs4M3/+fOh0OvnRpk0b124GERFQMuqUeQLZ/3wSxcajMEgmrNPMQyZa4C+F01AsAC8VEKi6BrUKKBIqPFmqplN1qW+r1dwpU8Aq4tRQVHkV3meffYZHHnkEoaGh8rEJEybI/x4ZGQmDwYD+/fvjzJkz6NChw+31tBbMmjUL06dPl59bLBYGUUTkmgIzsGoYLmb8BiFUCFTf2l5lvWYuNLDCo8xL5hQ953LwFODjhefua4eF205V2ra+rVZjmQJqjKo0AnXu3Dls27YNzz//fIXtoqKiAACnT58GAOj1eoeVcPbner2+wjb+/v7w8fFBcHAwPDw8nLYpfQ2r1Yrc3Nxy2zij1Wrh7++veBARVarADFw9jfMZ53CHKguAwAUpGF4qCcVCjdbqqwhRW6AqM5jyltdK3IXTLr3FklG9MfmhTg1ytRrLFFBjVKUA6vPPP0dISAgGDx5cYbvDhw8DAAyGkvnr6OhoHD16FJmZt5bxJiUlwd/fHxEREXKb7du3K66TlJSE6OhoAIBGo8Hdd9+taCNJErZv3y63ufvuu+Hl5aVoc/LkSZw/f15uQ0RULQrMkL4choufjcRLhZNxTgpBa3VJEJUpdPBUKTe4KxbALOvYUjlRCRUGUfagqG/7kums+CER8vGy7YD6uVqNZQqoMXI7gJIkCZ9//jnGjBkDT89bM4BnzpzBvHnzcODAAZw9exbfffcd/vznP6Nfv37o0aMHAGDAgAGIiIjAM888gyNHjmDr1q2YPXs2Jk2aBK1WCwB44YUX8Ntvv+H111/HiRMnsHTpUnz99deYNm2a/F7Tp0/Hp59+ii+++ALHjx/HxIkTcf36dTz33HMAAJ1Oh3HjxmH69On44YcfcODAATz33HOIjo52eQUeEZEr/rZxPzIyzuEOcRmLNIvxsvVWEBWiMju0vyJaYKfUq0xieQIinQRRzoKigd0NWDa6N/Q65WiNXuddb0sYNNTAj6gibpcx+O9//yvXXOrcubN8PCMjA6NHj0ZqaiquX7+ONm3a4PHHH8fs2bMVU2Hnzp3DxIkTsXPnTvj5+WHMmDF47733FMHYzp07MW3aNKSlpaF169aIi4tTJKsDwOLFi/HBBx/AZDKhZ8+eWLRokTxlCJQU0nzllVewdu1aFBYWIjY2FkuXLq1wCq8sljEgovJYiyX0iP8eBTbAgCys08xDmDoT56QQLC9+FPM1/3R4TbFQw1Ml4ZwUghHWOIQgp8I6UBUt4bdJAnvTs5GZV4CQ5iWjN/U9AKmoDlR9DPyo4aqN7+/bqgPV2DGAIiKFm7Wd3tllxqf/S1ec6oHTWKxZhLZqx6riVyQ/CHgiRG2WR53OSSEYbo1DS+TgKgJgRDBefqgjojsEN6igyF0NMfCjhqc2vr+5Fx4RkSsKzBBfDsNlYwY23XgTQJB8yoAsfKJZjCJ4KV5iEypkCh0M6lxckIJwQQpGa/VVFAk1LPDFdfjAdPM6fhoPTInp3OiDCXuZAqKGrsp1oIiImpIfUn5DxoVz0N+s7WRAFgDl9F17lXIvukyhwwvW6YrE8gtSME6ItphgnY483NrqakK/Do0+eCJqTBhAERFVYtPhi3jum0sYXhiHc1IIwtSZWKeZh96qX+XgqViooVIBRUKNKYUv4oIUBIM6V5FYnokWeNb6Op62zlbkOwX4emHyQ9VbTJOIahZzoCrAHCiiJq7AjI+2HMRHe29tSVV6xMnOnteUIbXEJOtLSEFHh8TyydbJOItQxaiT3fJ6unqOqKGq13vhERE1ZtZrOUhb8DAePzxBnq4DACOC8E7RKEXb34QB56QQ/Mk6Byk3K4sbEYQR1jicFyFoEXIHJg0bCC+/AMXrDDpvBk9EDRSTyImIypi3KRWbdx3EV5ocebpuhDUORgThLpzGEs3Hiva+sGKS9SUYoUyONiIId0z7AR7ezTHQW4eH7+7MFWhEjQRHoIiIShnyyf/w2a5zMN0cQSqd8/Swah/+T5sAL1XJPncTCqfhnBSCNuor+ESzWDFSBQDTYjrDI6A14K0DAG6US9SIMIAiIsrNgC1jP37/wQ4cvWiRDxsRhATrM7ggBSFMnYlPtQvl4OnJwgT8V/zOIcjSlwqi2gU75jsRUePAAIqImrbcDBR/cg+kfzwMXdZRxam7cBortAsRqLIojr9onYIjZXKdzkkhyII/rsNHbsfNcYkaLwZQRNQ0FZgB80W8/I/vIYoLFBv76pGFaKTK03U+KFK8dLbXaofE8uHWOIyxzkQefLk5LlETwACKiJqem1XFz334e+y76q3Y2Pff2gRs1r6BNdp34aWSIASgUgHnpBA8UZigmK4rHUSZECQHTwA3xyVq7BhAEVGT898Dp3E+45wcCGWiBZ4sTJA3+w1S5UGlgiJ4GmGNw0HRucKcJwDQ67yxjKUJiBo9ljEgoibDJgn84YMdOJ9TAAPi5EKX6zTzMK3oRZjhhyDkye0zREsIoZJLGAC3cp7WaeYpcp7G3tcOD0foWZqAqIlgJfIKsBI5UeOxYf8FTP2/I4pjzqqKl1YkVPhL4XTswN0O5/TIwnX44LrKF4tH9sKgHqE10m8ich8rkRMR3Y4CM5B5AkPf/coheNIjC37Ix5tFYxXHi4Uas6xjb+ZECfxduxB34bTDpe05T4tH9mbwRNQEcQqPiBqnAjPEF4/BeukoFosAPIV4eRrOgCys1ySgpcoMFZSD8FeEDjulXniysJ28Cu//tAl4ojABR3Frw98gPw3eebw7c52ImiiOQBFRo7Rp36+4ePE8tKpitFZfxXrNXBiQJQdPrdVZ0KqKoVHZIImSkSej1AIGdY4isbxIqFEIL1xFgHztQD8vJM/qz+CJqAljDlQFmANF1AAVmPGHd75DelGgIlgCgEyhgyQAvdosN78gBWGS9WVIUOEqWsg5UeekEAy3xqElcnAVATAiWC5RwFV2RPUbc6CIiNxgu5GLg+8+hJWqt2BAFowIwlPWBFyQSqbuQlRmOXgqFJ64IJWcP4JOOIqOTquKlxwPBsASBUR0C0egKsARKKKG4+s95/C3//yIr0qNINnLDzys2odPtQsV7UcXzsRpcQdMN/OiSrOvsMvDrb3s4gbfiWfvC2eJAqIGgCNQREQu6PTGZrz+n1SYSo0g2es7DVDtw1LNRw6vec/rHygvFLKvsCstuLmWwRMRyRhAEVGD1m7mZhRJt54bywRRK7QL4aUqGWjPFDqYpBYAoEgsdwU3Biai0hhAEVGDdPhsLtrN3Oz0nBFBeLtolOLYFaHDY4Vv43HrW3JOlD2IKrsdS2ncGJiInGEdKCJqcMoLnOwMyMIcr1WKY4Wi5OPOnlhurwNVejuWshrLxsA2SWBvejYy8woQ0tyb280QVQMGUETUYGRfs6L320kVtrFvz9JGfQUZUkt8UPQUXvf6Cq3VJcftieVPWhPQDPm4jECHfCc7vc4b8UMiGvSqu8RUI+ZuTIPRXCAfMzSCn4uornEVXgW4Co+o/ug6azMKKvm00iPL6Sq80nve2es7OVt9V1qQnwbJs/pD49lwMx0SU42YuOogyt421rOixo6r8IiIUDJlV1nwBADX4YMs+CuCJwBO6ztVJuu6FQfO5dxu1+uMTRKYuzHNIXgCIB+buzENNon/D01UFZzCI6J66/zVG+j31x9cbp8HX4yxzoQf8h1GmIwIwnBrnEN9p4pk5hVU3qie2puerZi2K0sAMJoLsDc9G9EdKh6NIyJHDKCIqF6qLFG8PHnwLTdAqmzarqyGXLrA1eDPZClA8pksJpgTuYkBFJGLbliLyz2nVqng7eVR423zrTYIp5MygAoq+Giq1ragyAapgnRIX41nrbaNmLO13NfcLh8vNd59PBLvJZ7AZUthue1a+WvR/Q5/xX8fb08PqG8GF9ZiCcWSVN7LofX0kAMRd9oW2SQU2cpvq/FQw9NDXWlbf2+vcq9R2lsbU5Fz49bPaNB5Y/bgO/GHriHlvqb0fzeipopJ5BVgEjmVVtGIyB+6tMTnz90jP78zLhH5RTanbaPCA/HVX6Ll573nJSH7utVp2x6tdfhu8v3y8/ve24GLuflO23YKaYak6Q/Kzx/+2484lXnNads7Anywe+ZD8vM/Lt6FlAtmp20D/TQ4GPew/Hz435OxJz3baVsfLw8cnzdQfv7c53vxw8krTtsCwNn3Bsv//uLqA9hy1FRu2/rgv9P6oXOr5gCAhUm/4uPtp8pt++2k+3BXmwAAwN9/PIP5358ot+3a8X3labR/JZ/FnG+Pldv2n8/2wUNdWwEA1u/PwGv/l1Ju2wBfL5hvFJUTRjunAiptX/q/G1F9xCRyImoydp26Wifv27K5pk7etzY8dXdrACh3yxpn+H/URK7hCFQFOAJFpXEKr+ba9p67Fdn55d+HmvD5s79DVPtAeKnV2H8uB5l5BQj01aBn24Byc4Aa0hSeve2245cd6kAF+noh+0ZRua+zs9+jsjiFR/VdbXx/86+AyEXufGnUVNvSQU91ti0dpNV22/YzN6P8EKDmWAqK5HtflVVoGk81NC4O4rvT1stDDS+P6ms7sLsBD0foFZXITeZ8TPv6SKXXL32PiEiJfxlEVCfyrTbcOSexzt6/Ia+wc5eHWqUIEpPPcANlotvFAIqIat1zK/fihxPlJ5fXJBVKtmhpypsD3xMeCIPOGyZzgdNJXt4josoxiZyIakeBGTBfxN1vbXUInvTIQnPcqPEuNJbNgW+Xh1qF+CERABwTzHmPiFzDAIqIal6BGdKXw3Duw99Dc+Oy4pTh5v51X2jeq/Ygqrm3cpBdr/NukPu/2SSB5DNZ+PbwRSSfyaqW7VcGdjdg2eje0OuU03QN9R4R1TZO4RFRjfto00E8nnEOYepMrNPMc7rJLyTAD/kub7Piir1vxOBwRm6DrrKdmGp0WEVn0HkjfkjEbQc5zhLMG+I9IqoLLGNQAZYxILo9Nkng3vnbcDnPqgiWzkkhmFb0IhZ6LZWfl978tzr079oSnz17T+UN67HEVCMmrjrokKdkD284UkTkXL0rpNmuXTuoVCqHx6RJkwAABQUFmDRpEoKCgtCsWTMMGzYMly8rh+vPnz+PwYMHw9fXFyEhIXjttddQXKys/7Jz50707t0bWq0WHTt2xMqVKx36smTJErRr1w7e3t6IiorC3r17Fedd6QsR1ZwtKUZ0eGMLLueVVFk3IggjrHE4J4UgTJ2Jb7QJNRY8AcDzD3So1uvVNpskMHdjmtMkb/uxuRvTqmU6j4jc51YAtW/fPhiNRvmRlJQEAHjqqacAANOmTcPGjRuxfv16/Pjjj7h06RKeeOIJ+fU2mw2DBw+G1WrFzz//jC+++AIrV67EnDlz5Dbp6ekYPHgw/vCHP+Dw4cOYOnUqnn/+eWzdemtvrK+++grTp09HfHw8Dh48iLvuuguxsbHIzMyU21TWFyKqOe9sPoYX1xx0OG5EEKYVvag4Nq3oxWoPngyNYAXZ3vRsxbRdWQKA0VyAveVsq0NENeu2pvCmTp2KTZs24dSpU7BYLGjZsiXWrFmDJ598EgBw4sQJ3HnnnUhOTkbfvn3x/fff49FHH8WlS5fQqlXJXk7Lly/HjBkzcOXKFWg0GsyYMQObN29Gamqq/D4jRoxAbm4uEhNLasZERUXhd7/7HRYvXgwAkCQJbdq0wUsvvYSZM2fCbDZX2hdXcAqPyH3xG47ii1/OOz2nyHm6qSZGoJY3gqmtbw9fxJR1hytt9/GInnis5x013yGiBqTeTeGVZrVasWrVKowdOxYqlQoHDhxAUVERYmJi5DZdu3ZF27ZtkZycDABITk5GZGSkHDwBQGxsLCwWC44dOya3KX0Nexv7NaxWKw4cOKBoo1arERMTI7dxpS/OFBYWwmKxKB5E5IICM6zZGeiZsNUheLKXKCibA/VEYYI8nbdOMw8GuFbcsSIqFbD06V4NMngqu9Iu2E/r0utY7JKoblR5Fd6GDRuQm5uLZ599FgBgMpmg0WgQEBCgaNeqVSuYTCa5TengyX7efq6iNhaLBfn5+cjJyYHNZnPa5sSJEy73xZn58+dj7ty5lf/wRFSiwAxYjLj4xTgU52XCxxqH3JsjSXpkoRny8Znmr7DAFwG4jjbqK4oRpxHWODmoWqeZh+HWOJhuYyRqycjeGNSj4QVPzlba6f29EeDrBfONIha7JKqHqjwC9dlnn+GRRx5BaGhodfanTs2aNQtms1l+ZGRk1HWXiOqvAjOwahjM/3gMIs+oGEkyIAv/p5mLzdo3EKbOhA7XkAs/h+m60onlWfDHdfhUqSsGnTeWj264wdPEVQcd8p0uWwqQezN4YrFLovqnSiNQ586dw7Zt2/DNN9/Ix/R6PaxWK3JzcxUjP5cvX4Zer5fblF0tZ18ZV7pN2dVyly9fhr+/P3x8fODh4QEPDw+nbUpfo7K+OKPVaqHVujZsTtTkFV7DtWwTdFYT8hCMC1IQwtSZWK9JgKdKgl6VAwC4IAVhuDUe1+ADP+Q7jDAZEYTh1jhch4/LNaBUAAL9NJg9+E7odT4NtnZRZSvtVAACfL2g9VTDZCmUz+mrqQ4UEVVdlUagPv/8c4SEhGDw4MHysbvvvhteXl7Yvn27fOzkyZM4f/48oqOjAQDR0dE4evSoYrVcUlIS/P39ERERIbcpfQ17G/s1NBoN7r77bkUbSZKwfft2uY0rfSGiqrMWS+i7OA0PZ7+Oc1IIWquvAlDBJLVAa3WWInh6ypoAI4KQB99yp+d6dY/A8nF/wLj72iHQz6vC97aHSe883h2P926N6A5BDTJ4AlxbaZdzowgf/qkn1o7vi49HlPxz14yHGDwR1TG3R6AkScLnn3+OMWPGwNPz1st1Oh3GjRuH6dOnIzAwEP7+/njppZcQHR0tr3obMGAAIiIi8Mwzz2DBggUwmUyYPXs2Jk2aJI/8vPDCC1i8eDFef/11jB07Fjt27MDXX3+NzZs3y+81ffp0jBkzBn369ME999yDjz76CNevX8dzzz3ncl+IyH02SeDltYew+ajx5hFlHlNZLxe9VOnqupg7W2LZ6D4AgPs6BeONwRFyZeyzV29g7d7zMFlK5QbV0OiLTRK1XpE7M6/84Km0q9cKudKOqJ5xO4Datm0bzp8/j7FjxzqcW7hwIdRqNYYNG4bCwkLExsZi6dKl8nkPDw9s2rQJEydORHR0NPz8/DBmzBi89dZbcpvw8HBs3rwZ06ZNw8cff4zWrVvjH//4B2JjY+U2w4cPx5UrVzBnzhyYTCb07NkTiYmJisTyyvpCRO5JTDXi5bUHYbUpj9trO32jTXB4zUKvpRWWKBj/QDu8Obib4piHWoXoDrfaT36oY40HNjW5XUpFXF1Bx5V2RPUPt3KpAOtAEZVITDXihVWOhTGBktpO6zVzb07jlTCJFigWarRWZzmt83Snvhm+nfwANJ51v595XW6XYpME7n9/B0zmggpX2u2a8VCDnaYkqgv1ug4UETUN1wqKMWm1a8GTSWqBC1LwzRwolZxYvk4zD/qbdZ78tB7Y9HK/ehE81fV2KR5qFeKHlOR/cqUdUcNS959gRFQv2SSBJ5bsQveErbA5iR/0NwtjtlZfRaHwxAUpCI9b38JT1nhFYvkFKUhRouDDp+6qNwFBfdguZWB3A5aN7g29TjlNp9d5c7NgonqsyoU0iajxSkw14sXVB1HRwMt1+CAL/oAEjLO+imvwkVfZ2RPLs+CP16wTkIlAXFf5YulIx4CgLpK37VxN4na1XVUN7G7AwxH6OrsPROQ+BlBEJLMWS3hl/SFsPFJ+xX67PPhijHWmy7Wdlo7s5VDosq6St+3qUxJ32eR5IqrfOIVHRACAud+movPs710Knuwqqu1kuln76VaVcOWuBeVV4DaZCzBx1UEkphpR0+4JD4RB5+2Qf2SnQklAx+1SiKgsjkAREX73dhKuXLNW6zUDfL2wZGRv9HVS6NKVCtxzN6bh4Qh9jU5j2ZO4J646CBWg6A+TuImoIhyBImrCbJLA7xdsq/bgCQBybxRBrVY5DT7qQ/K2HZO4iagqOAJF1ER9e+gipnx1uEbfo7zk6/qSvG3HJG4ichcDKKIm6NFFPyL10rUaf5/ykq/rU/K2HZO4icgdDKCImooCM2wFeei1MBWWQuV+LHpkKVbM3S57BW1nydc2SUCSBAJ8vJCbX+T264mI6gMGUERNQYEZOSuGwHLVCD9rHCylVs4ZbhbEzII/xlhnuhxExUaEYGua4wbCFSVfOytb4M7riYjqCyaREzUBi74/BMtVo7ytiuHmtir24ClMnYkgWOCHfJev+ex97bF8dG8YXEy+Lq9sQVlM3iaihoAjUESNVYEZ1hsWPL32HPZnXMdaxMnB0npNAmYWjcc7Xv9EmDpT3vC3vJpOZen9tXKStSvJ1xWVLbAL8PHCklG90be9Y9kDIqL6hgEUUWNUYMbFTwahOC8TF61xAIJgRBBGWOOwXpOA1uosrNK+BwBy8GR0MXgCgIJiCUlpJgzsbnAp+bqysgUAkJtfBLXKedkDIqL6hlN4RI3Qou8PoTgv02HKDgA8VZKi7bSiF90KngDAfKPIrWrh9a1sARHR7WIARdRYFJhhy72A978/jr/tuY4R1jick0JuTtnNxf2qFKzXzIVelaN42UKvpYoAyxX2qbi5G9Ngq2jH4ZvqY9kCIqLbwQCKqDHIzUDu8lhcWPgHbPhxHwDIU3ZGqQVaq69ilfY9tFZfBQBckILwRGGCHGCVHaVyhTvVwrnnHBE1NgygiBqyAjOQsR+Zf/8j/HJOIkx1KxjSIwu9cRItVWbFS0xSCzxlTcBB0VkxSrVOMw96N4MowLVpN/uecwAcgiiWLSCihohJ5EQNVYEZ+NdjsBlTESjZ4KmSUCTU8io7b5UVQciDqkxMUgwP+d/to1T2OlDX4eN2N1yddrPvOVe2DpRe5434IREsW0BEDYpKCFF5AkMTZbFYoNPpYDab4e/vX9fdIVKw5V7AtaX9obOaAADFQg1PlST/s7TLkg6vFE3Ee17/QGv1VYeVd1WpRG6vFr5rxkNujRzZJME954ioRtXG9zen8IgaGJsk8FHSr+j0/hEMtLyJC1JJEFRe8HRVNMdQ69vYJXrgKWu80yk7E4LcDp6Aqk272csePNbzDkR3YM0nImqYGEARNSCJqUZEJmzFR9tPQRIlU3BPWRMUQVRZBUIj/7t9yu6cFOLSlF2QnwZ/6RfucrVxIqKmglN4FeAUHtUbuRnYfTgNoxKLHU5F4jQMqmys0H7kcM4+IlWVKbtAPy/8MisGGk81p92IqEGpje9vJpET1Xe5GSj+5B7cU1yAu5CAI+gon7oLp/F/2nh4ONkkxR482RPL12nmYfjN7VpMCMJf+oVjxU/pDq+0h0XvPh4JjWfJILUr1caJiJoSTuER1XP/3PoLRHEBvFQS/k+bgLtwGsCt4MlLJWAfDBICuCo1B3ArJ8rrZhBlgS+uwwctfD2xfHRvzBoUgWVubAZMRES3cAqvApzCo7qUb7XhiaW7cdyUdzNYSpCDoTlFz+Itr8/hpbr151ss1JhQOA3H0U7e785+/LQIxXPW15Gn1eNg3MPyyBLAVXFE1PjUxvc3A6gKMICiuvLcP3/BD78qi1qWDqLsJFFS1+mK0GGidSpSbk7vGZCF9ZoEtFSZcUaEYpz1VRgRjBa+Xtg/+2EGSETUqDEHiqgpKTADhdfQ/cOjuGa1KU7pkYXfEIo5Rc9ivuaf8vG3ikbjf1IPXIcPTKU2BDYiCE9aE9AM+biMQDlZPOdGEfamZzOfiYjoNjGAIqoPcjMg1o1ChtGI5tY4XCsVDPXAaSzRfILr0KKD6pLiZW96rcGThZ1xBq0dLlk6oCrNla1XiIioYkwiJ6prBWbkrnwKxcajaKtSbux7F07j39oEtFFfQRfVBTkHapZ1LIpuJoiXTix3hatbrxARUfkYQBHVIZsk8Oa6ZJizs+TgyF5yYIBqn5zzJASgUgFFQo0nCxOwVorBk4UJiiAqspIgSgXAoCtJEiciotvDAIqojiSmGtEjYStWn7DJ1cFLB1ErtAvhpZJQLFQogJccPNnrQB1BRzmIKoQXriJAvnbZFPHb2XqFiIgccRVeBbgKj2pKYqoRL6w6qDhmQBbWaeYhTJ2pOD6hcBqOinAEIxdHSxXRtIvEaVxFAIwIBgBMi+mEdfsyYDTfynUy6LwRPySCtZ2IqElgGYM6xgCKaoJNErjvvR0wWRyTuR9W7cOn2oWKY2W3YSmPCiVFMHfNeAgAWNuJiJosljEgakTsBSv/lZzuNHi6C6exVPOx4ljpnKiKgihnU3QsVUBEVHOYA0VUC7akXEKft5Mw8tNf8H3qZYfzPcpUGh9fOM0hJ2qdZh7aeGRjTHQYAv00itdz+xUiotrFESiiGjbvu1R89vO5cs/rkYXFmkVysGRPFE+1tpdzoux72cU/GYWYXp0xZ0g3TtEREdUhBlBENcQmCcR8uBPpWTcqbHcdPiUr6CRgsvVleTsWI4IwwhqHdZp5uKbyxdVHP0dMr84AAA+1ilN0RER1iEnkFWASOVXVlpRLmLTmEFz942qOG/BDvtPq4R20ufj+tUHQNGtRvZ0kImqkmERO1ADN35KGv/+U7tZr8uAr71dX1mtPPcTgiYionnE7ifzixYsYPXo0goKC4OPjg8jISOzfv18+/+yzz0KlUikeAwcOVFwjOzsbo0aNgr+/PwICAjBu3Dhcu3ZN0SYlJQUPPPAAvL290aZNGyxYsMChL+vXr0fXrl3h7e2NyMhIbNmyRXFeCIE5c+bAYDDAx8cHMTExOHXqlLs/MpFLbJLA3/570u3gqTwBPl5YzsRwIqJ6ya0AKicnB/fddx+8vLzw/fffIy0tDR9++CFatFD+3/HAgQNhNBrlx9q1axXnR40ahWPHjiEpKQmbNm3CTz/9hAkTJsjnLRYLBgwYgLCwMBw4cAAffPABEhISsGLFCrnNzz//jJEjR2LcuHE4dOgQhg4diqFDhyI1NVVus2DBAixatAjLly/Hnj174Ofnh9jYWBQUcDNVql5bUkqqii/a4fqedJVZMorBExFRfeVWDtTMmTOxe/du/O9//yu3zbPPPovc3Fxs2LDB6fnjx48jIiIC+/btQ58+fQAAiYmJGDRoEC5cuIDQ0FAsW7YMb775JkwmEzQajfzeGzZswIkTJwAAw4cPx/Xr17Fp0yb52n379kXPnj2xfPlyCCEQGhqKV155Ba+++ioAwGw2o1WrVli5ciVGjBhR6c/LHChyRVWm7CpSuiAmV9YREbmvNr6/3RqB+u6779CnTx889dRTCAkJQa9evfDpp586tNu5cydCQkLQpUsXTJw4EVlZWfK55ORkBAQEyMETAMTExECtVmPPnj1ym379+snBEwDExsbi5MmTyMnJkdvExMQo3jc2NhbJyckAgPT0dJhMJkUbnU6HqKgouU1ZhYWFsFgsigdReWySwMKkX6s9eAK4Zx0RUX3nVgD122+/YdmyZejUqRO2bt2KiRMn4uWXX8YXX3whtxk4cCD+9a9/Yfv27Xj//ffx448/4pFHHoHNZgMAmEwmhISEKK7r6emJwMBAmEwmuU2rVq0UbezPK2tT+nzp1zlrU9b8+fOh0+nkR5s2bVy/OdSkJKYace/87fh4++3l1KnKxEgsiElE1DC4tQpPkiT06dMH7777LgCgV69eSE1NxfLlyzFmzBgAUEyNRUZGokePHujQoQN27tyJ/v37V2PXq9+sWbMwffp0+bnFYmEQRQ6cbQRcVUtG9kILPy0LYhIRNTBuBVAGgwERERGKY3feeSf+/e9/l/ua9u3bIzg4GKdPn0b//v2h1+uRmancbb64uBjZ2dnQ6/UAAL1ej8uXldtd2J9X1qb0efsxg8GgaNOzZ0+nfdVqtdBqteX+LET5VhumfnW4Wq419r52GNQjtFquRUREtcutKbz77rsPJ0+eVBz79ddfERYWVu5rLly4gKysLDmIiY6ORm5uLg4cOCC32bFjByRJQlRUlNzmp59+QlFRkdwmKSkJXbp0kVf8RUdHY/v27Yr3SkpKQnR0NAAgPDwcer1e0cZisWDPnj1yGyJ3zN+Shoj4RBQUSdVyvYcj9NVyHSIiqn1uBVDTpk3DL7/8gnfffRenT5/GmjVrsGLFCkyaNAkAcO3aNbz22mv45ZdfcPbsWWzfvh2PPfYYOnbsiNjYWAAlI1YDBw7E+PHjsXfvXuzevRuTJ0/GiBEjEBpa8n/jTz/9NDQaDcaNG4djx47hq6++wscff6yYXpsyZQoSExPx4Ycf4sSJE0hISMD+/fsxefJkAIBKpcLUqVPx9ttv47vvvsPRo0fx5z//GaGhoRg6dGh13DtqAmySQPKZLIxbuRd//ykd1VW336Arma4jIqKGye2tXDZt2oRZs2bh1KlTCA8Px/Tp0zF+/HgAQH5+PoYOHYpDhw4hNzcXoaGhGDBgAObNm6dI5s7OzsbkyZOxceNGqNVqDBs2DIsWLUKzZs3kNikpKZg0aRL27duH4OBgvPTSS5gxY4aiL+vXr8fs2bNx9uxZdOrUCQsWLMCgQYPk80IIxMfHY8WKFcjNzcX999+PpUuXonPnzi79rCxj0LQlphqR8N0xmCyF1XpdFcBEcSKiGlQb39/cC68CDKCarupMFC/NoPNG/JAIBk9ERDWIe+ER1QGbJDDzm6PVdr1mGjXm/rE7Qlv4cpUdEVEjwQCK6CabJLA3PRv/O3UFuTeKKn+Bi/76p54ccSIiamQYQBGhZMpu7sY0GM3Vt0+ir8YDf/vTXQyeiIgaIQZQ1KTZJIFPtp/CR7dZUdzOUw082iMUw3q1xr2dgjldR0TUSDGAoiYrMdWIGf9OgTm/uNquufhprq4jImoKGEBRk2OTBBbvOIWF26pn1Ang6joioqaGARQ1KYmpRsR/ewyX826vttPSp3ujhZ+Ge9gRETVRDKCo8SswA4XXkJihdqjtpEcWrsMHefB16VIcaSIiIoABFDV2BWaIL4ehwHwZCywzALSQTxmQhXWaeciCP8ZYZ5YbRAX6eSHu0W7Q+3OkiYiISri1Fx5RQ/NDym+4ePE8fK6dx+eYCwOyANwKnsLUmQiCBX7IL/ca7z4eicd73YHoDkEMnoiICAADKGrEElONeO6bS3iqYDbOSSEIU2dinWYeeqt+lYOnc1IIRljjYEKQ02tM7d+J03VEROSAARQ1StZiCa+sPwIAMCIII6xxchD1jTZBETwZywmeACC8pV9tdZmIiBoQBlDU6GxJMeLut5NwvdAmHzMiCNOKXlS0m1b0YoXBEwCENPeukT4SEVHDxgCKGpX5W9Lw4pqDyCtQFsc0IAsLvZYqji30WirnRJWlQsmKu3vCA2uqq0RE1IAxgKJGwSYJLEw6ib//lO5wrnTC+DkpBE8UJihyosoLouKHRDBpnIiInGIARQ2aPXDqkbAVH28/7XBeXyZ4GmGNw0HRWZETtU4zD/pSQZTeX4tlo7klCxERlY91oKjB2pJyCdO+PoLCYqncNtfhgyz4AxIUCeP2xHJ7Hajr8AEATIvpjMkPdeTIExERVUglhBB13Yn6ymKxQKfTwWw2w9/fv667Q6XM35LmdLrOmea4AT/kOy1VYK9E7uGrw3tPRHLUiYioEaiN72+OQFGDsyXF6HLwBAB58C23yrg9qFLdKKqWvhERUdPAHChqUGySwOxvU2vk2nM3psEmcUCWiIgqxwCKGgybJLBydzqyr1ur/doCgNFcgL3p2dV+bSIianw4hUf1mk0S2JuejW1pJvzn8EVkX3d/qq2FrxeG9gzF5z+fq7RtZl5BVbpJRERNDAMoqre2pBgx+9vU2xpxGtYrFAue6om96dkuBVCsPE5ERK5gAEX1jk0SeHntQWw+arqt6/hqPLDgqZ7wUKtwT3ggDDpvmMwFcJblpAKgZ+VxIiJyEXOgqF5JTDWie3zibQdPAPC3P90l13PyUKsQPyQCQEmwVJr9OSuPExGRqxhAUb2RmGrEC6sOIr+o/MKYrgjw8cRyJ5XEB3Y3YNno3tDrlNN0ep03K48TEZFbOIVH9YK1WMIrXx+p8uvv6xCEu9oE4L6OwejbPqjckaSB3Q14OEKPvenZyMwrQEjzkmk7jjwREZE7GEBRnbJJAot3nMKKn87gutX9kSd77tK/xkW5HAR5qFWI7uBYlZyIiMhVDKCoziSmGjHzm6PIvc0q4MxdIiKi2sYAiupEYqoRE1cddLoizlUGnTfih0Qwd4mIiGodAyiqdTZJYO7GtCoHT3/oEowJ/Toyd4mIiOoMAyiqVfbtWIzmqlX8fv6+dpg9pFs194qIiMg9DKCo1iSmGjF3Y1qVg6fxD4TjzcER1dwrIiIi9zGAolpxOzlPgX5eePux7hjUI7Ta+0VERFQVDKCoxt1OztMj3Vth8dN3M9eJiIjqFVYipxq3Nz27ytN2f44OZ/BERET1DkegqFrZJCFX+Q720wIqYOuxqu1rZ+DmvkREVE8xgKJqsyXlEmZ/m4rs67dXGJOb+xIRUX3HAIqqxfwtafj7T+nVci09C2QSEVE9xwCKbtvGI5eqHDypAAgA02I6oV2wHzf3JSKiBsHtJPKLFy9i9OjRCAoKgo+PDyIjI7F//375vBACc+bMgcFggI+PD2JiYnDq1CnFNbKzszFq1Cj4+/sjICAA48aNw7Vr1xRtUlJS8MADD8Db2xtt2rTBggULHPqyfv16dO3aFd7e3oiMjMSWLVsU513pC92eLSmX8PK6Q1V+vV7njeWje2NKTGc81vMORHcIYvBERET1nlsBVE5ODu677z54eXnh+++/R1paGj788EO0aNFCbrNgwQIsWrQIy5cvx549e+Dn54fY2FgUFNxahTVq1CgcO3YMSUlJ2LRpE3766SdMmDBBPm+xWDBgwACEhYXhwIED+OCDD5CQkIAVK1bIbX7++WeMHDkS48aNw6FDhzB06FAMHToUqampbvWFqm5LyiW8uOYQRBXqE/w5Ogxrx/fFrhkPcaqOiIgaHJUQrn/9zZw5E7t378b//vc/p+eFEAgNDcUrr7yCV199FQBgNpvRqlUrrFy5EiNGjMDx48cRERGBffv2oU+fPgCAxMREDBo0CBcuXEBoaCiWLVuGN998EyaTCRqNRn7vDRs24MSJEwCA4cOH4/r169i0aZP8/n379kXPnj2xfPlyl/pSGYvFAp1OB7PZDH9/f1dvU5OwJcWIyWsPQqrihnZrx/dFdIeg6u0UERERauf7260RqO+++w59+vTBU089hZCQEPTq1QuffvqpfD49PR0mkwkxMTHyMZ1Oh6ioKCQnJwMAkpOTERAQIAdPABATEwO1Wo09e/bIbfr16ycHTwAQGxuLkydPIicnR25T+n3sbezv40pfyiosLITFYlE8SMkmCXy87RReXFO14EkFlicgIqKGz60A6rfffsOyZcvQqVMnbN26FRMnTsTLL7+ML774AgBgMpXU+2nVqpXida1atZLPmUwmhISEKM57enoiMDBQ0cbZNUq/R3ltSp+vrC9lzZ8/HzqdTn60adOmslvSpCSmGnHfe9uxcNuvVXo9yxMQEVFj4dYqPEmS0KdPH7z77rsAgF69eiE1NRXLly/HmDFjaqSDtWnWrFmYPn26/NxisTCIQsmo0+Idp7Bw2+0l4LM8ARERNRZuBVAGgwERERGKY3feeSf+/e9/AwD0ej0A4PLlyzAYbn1JXr58GT179pTbZGZmKq5RXFyM7Oxs+fV6vR6XL19WtLE/r6xN6fOV9aUsrVYLrVZbwR1oerakGG8Wx7S6/VoVgJce6ogOIc1YnoCIiBoVt6bw7rvvPpw8eVJx7Ndff0VYWBgAIDw8HHq9Htu3b5fPWywW7NmzB9HR0QCA6Oho5Obm4sCBA3KbHTt2QJIkREVFyW1++uknFBXdqmidlJSELl26yCv+oqOjFe9jb2N/H1f6QhWbvyUNL645WKXgCQCWPN0L0wd0YXkCIiJqdNwKoKZNm4ZffvkF7777Lk6fPo01a9ZgxYoVmDRpEgBApVJh6tSpePvtt/Hdd9/h6NGj+POf/4zQ0FAMHToUQMmI1cCBAzF+/Hjs3bsXu3fvxuTJkzFixAiEhoYCAJ5++mloNBqMGzcOx44dw1dffYWPP/5YMb02ZcoUJCYm4sMPP8SJEyeQkJCA/fv3Y/LkyS73hcq3JaXqxTHVKmDp070wqEdoNfeKiIiofnCrjAEAbNq0CbNmzcKpU6cQHh6O6dOnY/z48fJ5IQTi4+OxYsUK5Obm4v7778fSpUvRuXNnuU12djYmT56MjRs3Qq1WY9iwYVi0aBGaNWsmt0lJScGkSZOwb98+BAcH46WXXsKMGTMUfVm/fj1mz56Ns2fPolOnTliwYAEGDRrkVl8q0hTLGNgkgV9+y8KEf+3HdautStdY+nRvDOrBPCciIqobtfH97XYA1ZQ0lQDKJgn8ciYLq/ecxY+nruJ6YdUCJwOTxImIqB6oje9v7oXXxCWmGjHzm6PIvVFUeeMKTIvphMkPdWKeExERNQkMoJqwLSlGvLjm4G1dQ++vRcIfu3HUiYiImhQGUE3UlpRLmLSm6psAA8DU/p3wUn+OOhERUdPDAKqJqa6imH/pF46pD7uWjE9ERNTYMIBqQhJTjUj4Lg0mS0GVrxHo54W3H+vOEgVERNSkMYBqIhJTjZi46iCquuQywNcLS0b2Rl8WxCQiImIA1djZSxTM/PfRKgdPAPDeE5G4r1NwtfWLiIioIWMA1Yjdzj52dgG+XnjviUiusiMiIiqFAVQjNX9LWpW3YgEAP40HJvTrgMkPdeSUHRERURkMoBqh29nHDgCm9u+Il/p3ZuBERERUDgZQjYxNEpj9bWqVXtuquQZzH+vO6ToiIqJKMIBqZPamZyP7etW2Zfnb8F64ryMTxYmIiCqjrusOUPXKzKt6jaer1wqrsSdERESNFwOoRiakuXedvJaIiKgpYQDVyNwTHgiDzr1ASAXAoPPGPeGBNdMpIiKiRoYBVCPjoVYhfkgEXF0/Z28XPySCq+6IiIhcxACqERrY3YBlo3s7jET5aT2g81GuG9DrvLFsdG+uvCMiInIDV+E1UgO7G/BwhB5707ORmVeAkOa3pujKHuPIExERkXsYQDViHmoVojsEORx3doyIiIhcxyk8IiIiIjcxgCIiIiJyEwMoIiIiIjcxgCIiIiJyEwMoIiIiIjcxgCIiIiJyEwMoIiIiIjexDlQdsEmCxSyJiIgaMAZQtSwx1Yi5G9NgNBfIxww6b8QPieB2KkRERA0Ep/BqUWKqERNXHVQETwBgMhdg4qqDSEw11lHPiIiIyB0MoGqJTRKYuzENwsk5+7G5G9Ngk5y1ICIiovqEAVQt2Zue7TDyVJoAYDQXYG96du11ioiIiKqEAVQtycwrP3iqSjsiIiKqOwygaklIc+9qbUdERER1hwFULbknPBAGnTfKK1agQslqvHvCA2uzW0RERFQFDKBqiYdahfghEQDgEETZn8cPiWA9KCIiogaAAVQtGtjdgGWje0OvU07T6XXeWDa6N+tAERERNRAspFnLBnY34OEIPSuRExERNWAMoOqAh1qF6A5Bdd0NIiIiqiJO4RERERG5iQEUERERkZvcCqASEhKgUqkUj65du8rnf//73zucf+GFFxTXOH/+PAYPHgxfX1+EhITgtddeQ3FxsaLNzp070bt3b2i1WnTs2BErV6506MuSJUvQrl07eHt7IyoqCnv37lWcLygowKRJkxAUFIRmzZph2LBhuHz5sjs/LhEREZFTbo9AdevWDUajUX7s2rVLcX78+PGK8wsWLJDP2Ww2DB48GFarFT///DO++OILrFy5EnPmzJHbpKenY/DgwfjDH/6Aw4cPY+rUqXj++eexdetWuc1XX32F6dOnIz4+HgcPHsRdd92F2NhYZGZmym2mTZuGjRs3Yv369fjxxx9x6dIlPPHEE+7+uERERESOhBvi4+PFXXfdVe75Bx98UEyZMqXc81u2bBFqtVqYTCb52LJly4S/v78oLCwUQgjx+uuvi27duileN3z4cBEbGys/v+eee8SkSZPk5zabTYSGhor58+cLIYTIzc0VXl5eYv369XKb48ePCwAiOTnZpZ9VCCHMZrMAIMxms8uvISIiorpVG9/fbo9AnTp1CqGhoWjfvj1GjRqF8+fPK86vXr0awcHB6N69O2bNmoUbN27I55KTkxEZGYlWrVrJx2JjY2GxWHDs2DG5TUxMjOKasbGxSE5OBgBYrVYcOHBA0UatViMmJkZuc+DAARQVFSnadO3aFW3btpXbOFNYWAiLxaJ4EBEREZXlVhmDqKgorFy5El26dIHRaMTcuXPxwAMPIDU1Fc2bN8fTTz+NsLAwhIaGIiUlBTNmzMDJkyfxzTffAABMJpMieAIgPzeZTBW2sVgsyM/PR05ODmw2m9M2J06ckK+h0WgQEBDg0Mb+Ps7Mnz8fc+fOdeeWEBERURPkVgD1yCOPyP/eo0cPREVFISwsDF9//TXGjRuHCRMmyOcjIyNhMBjQv39/nDlzBh06dKi+XteQWbNmYfr06fJzi8WCNm3a1GGPiIiIqD66rTIGAQEB6Ny5M06fPu30fFRUFADI5/V6vcNKOPtzvV5fYRt/f3/4+PggODgYHh4eTtuUvobVakVubm65bZzRarXw9/dXPIiIiIjKuq1K5NeuXcOZM2fwzDPPOD1/+PBhAIDBULLHW3R0NN555x1kZmYiJCQEAJCUlAR/f39ERETIbbZs2aK4TlJSEqKjowEAGo0Gd999N7Zv346hQ4cCACRJwvbt2zF58mQAwN133w0vLy9s374dw4YNAwCcPHkS58+fl6/jCiEEADAXioiIqAGxf2/bv8drhDsZ56+88orYuXOnSE9PF7t37xYxMTEiODhYZGZmitOnT4u33npL7N+/X6Snp4tvv/1WtG/fXvTr109+fXFxsejevbsYMGCAOHz4sEhMTBQtW7YUs2bNktv89ttvwtfXV7z22mvi+PHjYsmSJcLDw0MkJibKbdatWye0Wq1YuXKlSEtLExMmTBABAQGK1X0vvPCCaNu2rdixY4fYv3+/iI6OFtHR0W5l2GdkZAgAfPDBBx988MFHA3xkZGS49b3vDrdGoC5cuICRI0ciKysLLVu2xP33349ffvkFLVu2REFBAbZt24aPPvoI169fR5s2bTBs2DDMnj1bfr2Hhwc2bdqEiRMnIjo6Gn5+fhgzZgzeeustuU14eDg2b96MadOm4eOPP0br1q3xj3/8A7GxsXKb4cOH48qVK5gzZw5MJhN69uyJxMRERWL5woULoVarMWzYMBQWFiI2NhZLly5158dFaGgoMjIy0Lx5c6hUtzb7tedGZWRkcJoPvB9l8X444j1R4v1Q4v1wxHui5O79EEIgLy8PoaGhNdYnlRA1Ob7VOFksFuh0OpjNZv5ig/ejLN4PR7wnSrwfSrwfjnhPlOrj/eBeeERERERuYgBFRERE5CYGUFWg1WoRHx8PrVZb112pF3g/lHg/HPGeKPF+KPF+OOI9UaqP94M5UERERERu4ggUERERkZsYQBERERG5iQEUERERkZsYQBERERG5qdEFUAkJCVCpVIpH165d5fO///3vHc6/8MILimucP38egwcPhq+vL0JCQvDaa6+huLhY0Wbnzp3o3bs3tFotOnbsiJUrVzr0ZcmSJWjXrh28vb0RFRWFvXv3Ks4XFBRg0qRJCAoKQrNmzTBs2DCHTZKry8WLFzF69GgEBQXBx8cHkZGR2L9/v3xeCIE5c+bAYDDAx8cHMTExOHXqlOIa2dnZGDVqFPz9/REQEIBx48bh2rVrijYpKSl44IEH4O3tjTZt2mDBggUOfVm/fj26du0Kb29vREZGOux96Epfbldl9+PZZ591+D0ZOHCg4hqN5X60a9fO4WdVqVSYNGkSANd+Txvb30xl96SpfY7YbDbExcUhPDwcPj4+6NChA+bNm6fYZ6wpfYa4cj+a0mcIAOTl5WHq1KkICwuDj48P7r33Xuzbt8+tPjS4+1Fjm8TUkfj4eNGtWzdhNBrlx5UrV+TzDz74oBg/frzivNlsls/b9+uLiYkRhw4dElu2bBHBwcFO9+ubPn26SEtLE5988onT/fo0Go345z//KY4dOybGjx8vAgICxOXLl+U2L7zwgmjTpo3Yvn272L9/v+jbt6+49957q/2eZGdni7CwMPHss8+KPXv2iN9++01s3bpVnD59Wm7z3nvvCZ1OJzZs2CCOHDki/vjHP4rw8HCRn58vtxk4cKC46667xC+//CL+97//iY4dO4qRI0fK581ms2jVqpUYNWqUSE1NFWvXrhU+Pj7i73//u9xm9+7dwsPDQyxYsECkpaWJ2bNnCy8vL3H06FG3+lLT92PMmDFi4MCBit+T7OxsxXUay/3IzMxU/JxJSUkCgPjhhx+EEJX/njbGv5nK7klT+xx55513RFBQkNi0aZNIT08X69evF82aNRMff/yx3KYpfYa4cj+a0meIEEL86U9/EhEREeLHH38Up06dEvHx8cLf319cuHDB5T40tPvRKAOou+66q9zzDz74oJgyZUq557ds2SLUarViY+Jly5YJf39/UVhYKIQQ4vXXXxfdunVTvG748OEiNjZWfn7PPfeISZMmyc9tNpsIDQ0V8+fPF0IIkZubK7y8vMT69evlNsePHxcARHJysks/q6tmzJgh7r///nLPS5Ik9Hq9+OCDD+Rjubm5QqvVirVr1wohhEhLSxMAxL59++Q233//vVCpVOLixYtCCCGWLl0qWrRoId8n+3t36dJFfv6nP/1JDB48WPH+UVFR4i9/+YvLfbldld0PIUo+/B577LFyzzem+1HWlClTRIcOHYQkSS79njbGv5mySt8TIZre58jgwYPF2LFjFceeeOIJMWrUKCFE0/sMqex+CNG0PkNu3LghPDw8xKZNmxTHe/fuLd58881G+/vR6KbwAODUqVMIDQ1F+/btMWrUKJw/f15xfvXq1QgODkb37t0xa9Ys3LhxQz6XnJyMyMhIxcbEsbGxsFgsOHbsmNwmJiZGcc3Y2FgkJycDAKxWKw4cOKBoo1arERMTI7c5cOAAioqKFG26du2Ktm3bym2qy3fffYc+ffrgqaeeQkhICHr16oVPP/1UPp+eng6TyaToi06nQ1RUlNyX5ORkBAQEoE+fPnKbmJgYqNVq7NmzR27Tr18/aDQauU1sbCxOnjyJnJwcuU1F986VvtT0/bDbuXMnQkJC0KVLF0ycOBFZWVnyucZ0P0qzWq1YtWoVxo4dC5VK5dLvaWP8mymt7D2xa0qfI/feey+2b9+OX3/9FQBw5MgR7Nq1C4888giApvcZUtn9sGsqnyHFxcWw2Wzw9vZWHPfx8cGuXbsa7e+Hp1utG4CoqCisXLkSXbp0gdFoxNy5c/HAAw8gNTUVzZs3x9NPP42wsDCEhoYiJSUFM2bMwMmTJ/HNN98AAEwmk+JDD4D83GQyVdjGYrEgPz8fOTk5sNlsTtucOHFCvoZGo0FAQIBDG/v7VJfffvsNy5Ytw/Tp0/HGG29g3759ePnll6HRaDBmzBj5/Zz1t/TPHBISojjv6emJwMBARZvw8HCHa9jPtWjRotx7V/oalfXldlV2PwBg4MCBeOKJJxAeHo4zZ87gjTfewCOPPILk5GR4eHg0qvtR2oYNG5Cbm4tnn31Wfv/Kfk8b499MaWXvCYAm9zkyc+ZMWCwWdO3aFR4eHrDZbHjnnXcwatQoxc/UVD5DKrsfQNP6DGnevDmio6Mxb9483HnnnWjVqhXWrl2L5ORkdOzYsdH+fjS6AKr0/wH06NEDUVFRCAsLw9dff41x48ZhwoQJ8vnIyEgYDAb0798fZ86cQYcOHeqiyzVOkiT06dMH7777LgCgV69eSE1NxfLly+WAoSlx5X6MGDFCbh8ZGYkePXqgQ4cO2LlzJ/r3718n/a4Nn332GR555BGEhobWdVfqDWf3pKl9jnz99ddYvXo11qxZg27duuHw4cOYOnUqQkNDm+RniCv3o6l9hnz55ZcYO3Ys7rjjDnh4eKB3794YOXIkDhw4UNddqzGNcgqvtICAAHTu3BmnT592ej4qKgoA5PN6vd5hBYv9uV6vr7CNv78/fHx8EBwcDA8PD6dtSl/DarUiNze33DbVxWAwICIiQnHszjvvlKc27e9XWX8zMzMV54uLi5GdnV3pfSn9HuW1KX2+sr7crsruhzPt27dHcHCw4veksdwPu3PnzmHbtm14/vnn5WOu/J42xr8ZO2f3xJnG/jny2muvYebMmRgxYgQiIyPxzDPPYNq0aZg/f77iZ2oqnyGV3Q9nGvtnSIcOHfDjjz/i2rVryMjIwN69e1FUVIT27ds32t+PRh9AXbt2DWfOnIHBYHB6/vDhwwAgn4+OjsbRo0cV/yGTkpLg7+8vf+lGR0dj+/btiuskJSUhOjoaAKDRaHD33Xcr2kiShO3bt8tt7r77bnh5eSnanDx5EufPn5fbVJf77rsPJ0+eVBz79ddfERYWBgAIDw+HXq9X9MVisWDPnj1yX6Kjo5Gbm6v4v4kdO3ZAkiT5yyM6Oho//fQTioqK5DZJSUno0qULWrRoIbep6N650pfbVdn9cObChQvIyspS/J40lvth9/nnnyMkJASDBw+Wj7nye9oY/2bsnN0TZxr758iNGzegViu/Ljw8PCBJEoCm9xlS2f1wpil8hgCAn58fDAYDcnJysHXrVjz22GON9/fDrZTzBuCVV14RO3fuFOnp6WL37t0iJiZGBAcHi8zMTHH69Gnx1ltvif3794v09HTx7bffivbt24t+/frJr7cvPx4wYIA4fPiwSExMFC1btnS6/Pi1114Tx48fF0uWLHG6/Fir1YqVK1eKtLQ0MWHCBBEQEKBYlfPCCy+Itm3bih07doj9+/eL6OhoER0dXe33ZO/evcLT01O888474tSpU2L16tXC19dXrFq1Sm7z3nvviYCAAPHtt9+KlJQU8dhjjzldYtqrVy+xZ88esWvXLtGpUyfFEtPc3FzRqlUr8cwzz4jU1FSxbt064evr67DE1NPTU/z1r38Vx48fF/Hx8U6XmFbWl5q8H3l5eeLVV18VycnJIj09XWzbtk307t1bdOrUSRQUFDS6+yFEyequtm3bihkzZjicq+z3tDH+zVR0T5ri58iYMWPEHXfcIS/b/+abb0RwcLB4/fXX5TZN6TOksvvRFD9DEhMTxffffy9+++038d///lfcddddIioqSlitVpf70NDuR6MLoIYPHy4MBoPQaDTijjvuEMOHD5fr+5w/f17069dPBAYGCq1WKzp27Chee+01Rf0WIYQ4e/aseOSRR4SPj48IDg4Wr7zyiigqKlK0+eGHH0TPnj2FRqMR7du3F59//rlDXz755BPRtm1bodFoxD333CN++eUXxfn8/Hzx4osvihYtWghfX1/x+OOPC6PRWL035KaNGzeK7t27C61WK7p27SpWrFihOC9JkoiLixOtWrUSWq1W9O/fX5w8eVLRJisrS4wcOVI0a9ZM+Pv7i+eee07k5eUp2hw5ckTcf//9QqvVijvuuEO89957Dn35+uuvRefOnYVGoxHdunUTmzdvdrsvt6ui+3Hjxg0xYMAA0bJlS+Hl5SXCwsLE+PHjFV9aQjSu+7F161YBwOl1Xfk9bYx/M+Xdk6b4OWKxWMSUKVNE27Zthbe3t2jfvr148803FcvJm9JnSGX3oyl+hnz11Veiffv2QqPRCL1eLyZNmiRyc3Pd6kNDux8qIUqVTiUiIiKiSjX6HCgiIiKi6sYAioiIiMhNDKCIiIiI3MQAioiIiMhNDKCIiIiI3MQAioiIiMhNDKCIiIiI3MQAioiIiMhNDKCIiIiI3MQAioiIiMhNDKCIiIiI3MQAioiIiMhN/w8YE40i3BykjAAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "reclassifying HD 0\n",
      "reclassifying HD 886\n",
      "reclassifying HD 1694\n",
      "reclassifying HD 2588\n",
      "reclassifying HD 3802\n",
      "There are 72 HDs still with both discontinuity problems\n",
      "Additionally, 2118 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%200 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for i, t in enumerate(sPgenerator):    \n",
    "    if i%500 == 0:\n",
    "        print(\"reclassifying HD\",t)\n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 185,
   "id": "4037f8cb-661b-4032-bfb9-e147975e3bbb",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1/13/24 - classify further: ID those with adjoiners intersecting the map boundary vs internal islands\n",
      "working on enclave-generating HD 4\n",
      "working on enclave-generating HD 1241\n",
      "working on enclave-generating HD 2393\n",
      "working on enclave-generating HD 3395\n",
      "working on enclave-generating HD 171\n",
      "working on enclave-generating HD 1080\n",
      "working on enclave-generating HD 2042\n",
      "working on enclave-generating HD 2915\n",
      "working on enclave-generating HD 4108\n",
      "Out of 4001 HDpolys that generated enclaves, 0 had contiguous adjrs, while 3391 neighbored a state boundary while 610 had only internal enclaves\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 to print the total enclave pops for all enclavy HDs.  This takes a few min; not required 0\n"
     ]
    }
   ],
   "source": [
    "print(\"1/13/24 - classify further: ID those with adjoiners intersecting the map boundary vs internal islands\")\n",
    "internals, edgers, nOK = list(), list(), 0\n",
    "for i,t in enumerate(eLgenerator):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on enclave-generating HD\",t)\n",
    "    twoNbrs = get2nbrs(HDunitList[t],unitNbrs)\n",
    "    isContig, adjSublist = isContiguous(twoNbrs,unitNbrs)\n",
    "    if isContig:\n",
    "        nOK +=1\n",
    "    else:\n",
    "        if len (set(getAdjoiners(HDunitList[t],unitNbrs)).intersection(set(borderUnits)))  > 0:\n",
    "            edgers.append(t)\n",
    "        else:\n",
    "            internals.append(t)\n",
    "print(\"Out of\",len(eLgenerator),\"HDpolys that generated enclaves,\",nOK,\"had contiguous adjrs, while\",len(edgers),\n",
    "      \"neighbored a state boundary while\",len(internals),\"had only internal enclaves\")\n",
    " \n",
    "plotEnclaves = input(\"enter 1 to print the total enclave pops for all enclavy HDs.  This takes a few min; not required\")\n",
    "if str(plotEnclaves) == str(1):\n",
    "    for i,t in enumerate(internals): \n",
    "        if i%500 == 0:\n",
    "            print(\"computing full enclave lists for HD\",t)\n",
    "        fullEnclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        tEpop = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in fullEnclaveLists ] ) \n",
    "        plt.scatter(HDvPop[t],tEpop)\n",
    "    plt.plot([aDP,aDP],[0,5000],ls=\"--\")\n",
    "    print(\"Here are the total enclave pops for enclaving HDs not touching the state boundary vs. the original HD pop\")\n",
    "    plt.show()    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 186,
   "id": "05f929ce-4f94-47a6-baf4-60c5a89e2ae5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 748977 district pop vs 713311 target\n",
      "working on enclave-y HD 152 . We have evaluated 0 of 4001 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 3141 . We have evaluated 100 of 4001 enclavy HDs.Time is now 10\n",
      "working on enclave-y HD 3342 . We have evaluated 200 of 4001 enclavy HDs.Time is now 20\n",
      "working on enclave-y HD 3472 . We have evaluated 300 of 4001 enclavy HDs.Time is now 31\n",
      "working on enclave-y HD 3593 . We have evaluated 400 of 4001 enclavy HDs.Time is now 41\n",
      "working on enclave-y HD 2717 . We have evaluated 500 of 4001 enclavy HDs.Time is now 58\n",
      "working on enclave-y HD 3875 . We have evaluated 600 of 4001 enclavy HDs.Time is now 77\n",
      "working on enclave-y HD 283 . We have evaluated 700 of 4001 enclavy HDs.Time is now 95\n",
      "working on enclave-y HD 475 . We have evaluated 800 of 4001 enclavy HDs.Time is now 108\n",
      "working on enclave-y HD 685 . We have evaluated 900 of 4001 enclavy HDs.Time is now 124\n",
      "working on enclave-y HD 905 . We have evaluated 1000 of 4001 enclavy HDs.Time is now 139\n",
      "working on enclave-y HD 1216 . We have evaluated 1100 of 4001 enclavy HDs.Time is now 153\n",
      "working on enclave-y HD 1422 . We have evaluated 1200 of 4001 enclavy HDs.Time is now 164\n",
      "working on enclave-y HD 1692 . We have evaluated 1300 of 4001 enclavy HDs.Time is now 180\n",
      "working on enclave-y HD 1918 . We have evaluated 1400 of 4001 enclavy HDs.Time is now 194\n",
      "working on enclave-y HD 2155 . We have evaluated 1500 of 4001 enclavy HDs.Time is now 208\n",
      "working on enclave-y HD 2443 . We have evaluated 1600 of 4001 enclavy HDs.Time is now 224\n",
      "working on enclave-y HD 2747 . We have evaluated 1700 of 4001 enclavy HDs.Time is now 238\n",
      "working on enclave-y HD 2996 . We have evaluated 1800 of 4001 enclavy HDs.Time is now 250\n",
      "working on enclave-y HD 3735 . We have evaluated 1900 of 4001 enclavy HDs.Time is now 263\n",
      "working on enclave-y HD 3962 . We have evaluated 2000 of 4001 enclavy HDs.Time is now 275\n",
      "working on enclave-y HD 97 . We have evaluated 2100 of 4001 enclavy HDs.Time is now 292\n",
      "working on enclave-y HD 256 . We have evaluated 2200 of 4001 enclavy HDs.Time is now 306\n",
      "working on enclave-y HD 471 . We have evaluated 2300 of 4001 enclavy HDs.Time is now 322\n",
      "working on enclave-y HD 670 . We have evaluated 2400 of 4001 enclavy HDs.Time is now 343\n",
      "working on enclave-y HD 865 . We have evaluated 2500 of 4001 enclavy HDs.Time is now 359\n",
      "working on enclave-y HD 1021 . We have evaluated 2600 of 4001 enclavy HDs.Time is now 377\n",
      "working on enclave-y HD 1181 . We have evaluated 2700 of 4001 enclavy HDs.Time is now 396\n",
      "working on enclave-y HD 1353 . We have evaluated 2800 of 4001 enclavy HDs.Time is now 412\n",
      "working on enclave-y HD 1522 . We have evaluated 2900 of 4001 enclavy HDs.Time is now 428\n",
      "working on enclave-y HD 1689 . We have evaluated 3000 of 4001 enclavy HDs.Time is now 446\n",
      "working on enclave-y HD 1924 . We have evaluated 3100 of 4001 enclavy HDs.Time is now 464\n",
      "working on enclave-y HD 2148 . We have evaluated 3200 of 4001 enclavy HDs.Time is now 478\n",
      "working on enclave-y HD 2306 . We have evaluated 3300 of 4001 enclavy HDs.Time is now 501\n",
      "working on enclave-y HD 2523 . We have evaluated 3400 of 4001 enclavy HDs.Time is now 518\n",
      "working on enclave-y HD 2668 . We have evaluated 3500 of 4001 enclavy HDs.Time is now 536\n",
      "working on enclave-y HD 2910 . We have evaluated 3600 of 4001 enclavy HDs.Time is now 555\n",
      "working on enclave-y HD 3169 . We have evaluated 3700 of 4001 enclavy HDs.Time is now 578\n",
      "working on enclave-y HD 3741 . We have evaluated 3800 of 4001 enclavy HDs.Time is now 599\n",
      "working on enclave-y HD 3986 . We have evaluated 3900 of 4001 enclavy HDs.Time is now 614\n",
      "working on enclave-y HD 4108 . We have evaluated 4000 of 4001 enclavy HDs.Time is now 624\n",
      "Out of 4001 HDs with enclaves 4001 had enclaves.\n",
      "Of these, 3851 wouldn't be over 748977 if all enclaves filled, while 150 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "### THIS IS THE \"CANFILL\" CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(internals + edgers):\n",
    "    if iii%100 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 187,
   "id": "8987ad1f-d372-415d-a2ec-8fc6736c5102",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "610 3391 2189 1969\n",
      "150 150 3851\n"
     ]
    }
   ],
   "source": [
    "print(len(internals),len(edgers),len(doubleTroubleList),len(set(edgers).intersection(set(doubleTroubleList))))\n",
    "print(len(set(edgers).difference(set(canFill))) ,len(cantFill) , len(canFill))\n",
    "#610 3379 2187 1954\n",
    "#80 80 3909  for original MN option3 (assigned CCBs by captured area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "id": "8fa887be-92e6-422a-8e80-e00fd3265aab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.02404 0.13177\n",
      "CCB cluster 0 = unit 2725 with pop 314005.0 now has use of 1.0048355435053267\n",
      "CCB cluster 1 = unit 2726 with pop 148064.0 now has use of 1.000241479269026\n",
      "CCB cluster 2 = unit 2727 with pop 216736.0 now has use of 1.0021382656320768\n",
      "CCB cluster 3 = unit 2728 with pop 65226.0 now has use of 1.001220013549454\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "id": "e9d50ef8-39b2-4e22-a11e-cabeda78721e",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "id": "b759b3c7-b8a3-4d2c-a8fe-50fa93b3e940",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dunRRZmamvvvuO6dm4sSJ2r59u4qKirRy5UoVFxdr+vTpTnsoFFJGRoaSk5NVWlqqBQsWqKCgQC+88MJZPEQAANDeeYwx5qx39nj0u9/9Tj/72c8k/fXdncTERD3wwAN68MEHJUm1tbWKj4/X0qVLNW7cOH322WcaMGCANm/erBEjRkiSVq1apeuuu05ff/21EhMTtXjxYj366KMKBoPyer2SpIcfflgrVqzQ559/fkZjC4VCio6OVm1trfx+/9k+RAA/QK+H3w5b33vmZYetbwBtJ1yv3616DU9lZaWCwaDS09OdbdHR0UpNTVVJSYkkqaSkRDExMU7YkaT09HRFRERo48aNTs2oUaOcsCNJmZmZqqio0MGDB5s9dn19vUKhkGsBAACQWjnwBINBSVJ8fLxre3x8vNMWDAYVFxfnau/QoYO6d+/uqmmujxOP8bcKCwsVHR3tLElJST/8AQEAACtYc5dWfn6+amtrneWrr75q6yEBAIBzRKsGnkAgIEmqrq52ba+urnbaAoGA9u3b52pvaGjQgQMHXDXN9XHiMf6Wz+eT3+93LQAAAFIrB57evXsrEAho7dq1zrZQKKSNGzcqLS1NkpSWlqaamhqVlpY6NevWrVNTU5NSU1OdmuLiYh07dsypKSoqUr9+/dStW7fWHDIAAGgHWhx46urqVFZWprKyMkl/vVC5rKxMVVVV8ng8uv/++/Uv//Iv+v3vf6+tW7dq8uTJSkxMdO7kuvTSSzVmzBhNmzZNmzZt0ocffqgZM2Zo3LhxSkxMlCRNmDBBXq9XU6dO1fbt27V8+XI9++yzys3NbbUHDgAA2o8OLd1hy5Ytuvbaa5314yFkypQpWrp0qR566CEdPnxY06dPV01Nja666iqtWrVKnTp1cvZZtmyZZsyYodGjRysiIkJjx47Vb37zG6c9Ojpaq1evVk5OjoYPH67Y2FjNnj3b9V09AAAAZ+oHfQ/PuYzv4QHaHt/DA6Clzovv4QEAADgXEXgAAID1CDwAAMB6BB4AAGA9Ag8AALAegQcAAFiPwAMAAKxH4AEAANYj8AAAAOsReAAAgPUIPAAAwHoEHgAAYD0CDwAAsB6BBwAAWI/AAwAArEfgAQAA1iPwAAAA6xF4AACA9Qg8AADAegQeAABgPQIPAACwHoEHAABYj8ADAACsR+ABAADWI/AAAADrEXgAAID1CDwAAMB6BB4AAGA9Ag8AALAegQcAAFiPwAMAAKxH4AEAANYj8AAAAOsReAAAgPUIPAAAwHoEHgAAYD0CDwAAsB6BBwAAWI/AAwAArEfgAQAA1mv1wNOrVy95PJ6TlpycHEnSNddcc1LbXXfd5eqjqqpK2dnZioqKUlxcnGbNmqWGhobWHioAAGgnOrR2h5s3b1ZjY6Ozvm3bNv3jP/6jfv7znzvbpk2bprlz5zrrUVFRzr8bGxuVnZ2tQCCgjz76SHv37tXkyZPVsWNHPf300609XAAA0A60euC58MILXevz5s1T3759dfXVVzvboqKiFAgEmt1/9erV2rFjh9asWaP4+HhddtllevLJJ5WXl6eCggJ5vd7WHjIAALBcWK/hOXr0qF5++WXdcccd8ng8zvZly5YpNjZWgwYNUn5+vo4cOeK0lZSUKCUlRfHx8c62zMxMhUIhbd++/ZTHqq+vVygUci0AAABSGN7hOdGKFStUU1Oj2267zdk2YcIEJScnKzExUeXl5crLy1NFRYXefPNNSVIwGHSFHUnOejAYPOWxCgsLNWfOnNZ/EAAA4LwX1sDz4osvKisrS4mJic626dOnO/9OSUlRQkKCRo8erd27d6tv375nfaz8/Hzl5uY666FQSElJSWfdHwAAsEfYAs+XX36pNWvWOO/cnEpqaqokadeuXerbt68CgYA2bdrkqqmurpakU173I0k+n08+n+8HjhoAANgobNfwvPTSS4qLi1N2dvb31pWVlUmSEhISJElpaWnaunWr9u3b59QUFRXJ7/drwIAB4RouAACwWFje4WlqatJLL72kKVOmqEOH/z/E7t279corr+i6665Tjx49VF5erpkzZ2rUqFEaPHiwJCkjI0MDBgzQpEmTNH/+fAWDQT322GPKycnhHRwAAHBWwhJ41qxZo6qqKt1xxx2u7V6vV2vWrNEzzzyjw4cPKykpSWPHjtVjjz3m1ERGRmrlypW6++67lZaWpi5dumjKlCmu7+0BAABoibAEnoyMDBljTtqelJSkDRs2nHb/5ORkvfPOO+EYGgAAaIf4LS0AAGA9Ag8AALAegQcAAFiPwAMAAKxH4AEAANYj8AAAAOsReAAAgPUIPAAAwHoEHgAAYD0CDwAAsB6BBwAAWI/AAwAArEfgAQAA1iPwAAAA6xF4AACA9Qg8AADAegQeAABgPQIPAACwHoEHAABYj8ADAACsR+ABAADWI/AAAADrEXgAAID1CDwAAMB6BB4AAGA9Ag8AALAegQcAAFiPwAMAAKxH4AEAANYj8AAAAOsReAAAgPUIPAAAwHoEHgAAYD0CDwAAsB6BBwAAWI/AAwAArEfgAQAA1iPwAAAA6xF4AACA9Qg8AADAeq0eeAoKCuTxeFxL//79nfbvvvtOOTk56tGjhy644AKNHTtW1dXVrj6qqqqUnZ2tqKgoxcXFadasWWpoaGjtoQIAgHaiQzg6HThwoNasWfP/B+nw/4eZOXOm3n77bb3xxhuKjo7WjBkzdNNNN+nDDz+UJDU2Nio7O1uBQEAfffSR9u7dq8mTJ6tjx456+umnwzFcAABgubAEng4dOigQCJy0vba2Vi+++KJeeeUV/cM//IMk6aWXXtKll16qjz/+WFdccYVWr16tHTt2aM2aNYqPj9dll12mJ598Unl5eSooKJDX6w3HkAEAgMXCcg3Pzp07lZiYqD59+mjixImqqqqSJJWWlurYsWNKT093avv376+ePXuqpKREklRSUqKUlBTFx8c7NZmZmQqFQtq+ffspj1lfX69QKORaAAAApDAEntTUVC1dulSrVq3S4sWLVVlZqZEjR+rQoUMKBoPyer2KiYlx7RMfH69gMChJCgaDrrBzvP1426kUFhYqOjraWZKSklr3gQEAgPNWq3+klZWV5fx78ODBSk1NVXJysl5//XV17ty5tQ/nyM/PV25urrMeCoUIPQAAQNLf4bb0mJgYXXLJJdq1a5cCgYCOHj2qmpoaV011dbVzzU8gEDjprq3j681dF3Scz+eT3+93LQAAANLfIfDU1dVp9+7dSkhI0PDhw9WxY0etXbvWaa+oqFBVVZXS0tIkSWlpadq6dav27dvn1BQVFcnv92vAgAHhHi4AALBQq3+k9eCDD+r6669XcnKyvvnmGz3xxBOKjIzU+PHjFR0dralTpyo3N1fdu3eX3+/XPffco7S0NF1xxRWSpIyMDA0YMECTJk3S/PnzFQwG9dhjjyknJ0c+n6+1hwsAANqBVg88X3/9tcaPH6/9+/frwgsv1FVXXaWPP/5YF154oSTp17/+tSIiIjR27FjV19crMzNTv/3tb539IyMjtXLlSt19991KS0tTly5dNGXKFM2dO7e1hwoAANoJjzHGtPUgwiEUCik6Olq1tbVczwO0kV4Pvx22vvfMyw5b3wDaTrhev/ktLQAAYD0CDwAAsF5YfloCwPklnB89AcC5gHd4AACA9Qg8AADAegQeAABgPQIPAACwHoEHAABYj8ADAACsR+ABAADWI/AAAADrEXgAAID1CDwAAMB6BB4AAGA9Ag8AALAegQcAAFiPwAMAAKxH4AEAANYj8AAAAOsReAAAgPUIPAAAwHoEHgAAYD0CDwAAsB6BBwAAWI/AAwAArEfgAQAA1iPwAAAA6xF4AACA9Qg8AADAegQeAABgPQIPAACwHoEHAABYj8ADAACsR+ABAADWI/AAAADrEXgAAID1CDwAAMB6Hdp6AADQXvR6+O2w9LtnXnZY+gVswjs8AADAegQeAABgvVYPPIWFhfrJT36irl27Ki4uTj/72c9UUVHhqrnmmmvk8Xhcy1133eWqqaqqUnZ2tqKiohQXF6dZs2apoaGhtYcLAADagVa/hmfDhg3KycnRT37yEzU0NOiRRx5RRkaGduzYoS5dujh106ZN09y5c531qKgo59+NjY3Kzs5WIBDQRx99pL1792ry5Mnq2LGjnn766dYeMgAAsFyrB55Vq1a51pcuXaq4uDiVlpZq1KhRzvaoqCgFAoFm+1i9erV27NihNWvWKD4+XpdddpmefPJJ5eXlqaCgQF6vt7WHDQAALBb2a3hqa2slSd27d3dtX7ZsmWJjYzVo0CDl5+fryJEjTltJSYlSUlIUHx/vbMvMzFQoFNL27dubPU59fb1CoZBrAQAAkMJ8W3pTU5Puv/9+/fSnP9WgQYOc7RMmTFBycrISExNVXl6uvLw8VVRU6M0335QkBYNBV9iR5KwHg8Fmj1VYWKg5c+aE6ZEAAIDzWVgDT05OjrZt26YPPvjAtX369OnOv1NSUpSQkKDRo0dr9+7d6tu371kdKz8/X7m5uc56KBRSUlLS2Q0cAABYJWwfac2YMUMrV67Ue++9px/96EffW5uamipJ2rVrlyQpEAiourraVXN8/VTX/fh8Pvn9ftcCAAAghSHwGGM0Y8YM/e53v9O6devUu3fv0+5TVlYmSUpISJAkpaWlaevWrdq3b59TU1RUJL/frwEDBrT2kAEAgOVa/SOtnJwcvfLKK3rrrbfUtWtX55qb6Ohode7cWbt379Yrr7yi6667Tj169FB5eblmzpypUaNGafDgwZKkjIwMDRgwQJMmTdL8+fMVDAb12GOPKScnRz6fr7WHDAAALNfq7/AsXrxYtbW1uuaaa5SQkOAsy5cvlyR5vV6tWbNGGRkZ6t+/vx544AGNHTtWf/jDH5w+IiMjtXLlSkVGRiotLU233nqrJk+e7PreHgAAgDPV6u/wGGO+tz0pKUkbNmw4bT/Jycl65513WmtYAACgHePX0gGcl/jlcQAtwY+HAgAA6xF4AACA9Qg8AADAegQeAABgPQIPAACwHndpAcAJwnX3F4C2xTs8AADAegQeAABgPQIPAACwHoEHAABYj8ADAACsR+ABAADWI/AAAADr8T08wHmC74cBgLNH4AEAoI2F839o9szLDlvf5xMCDwDAKoQHNIfAAwBoE+fjx7Tn45jxVwQeADjP8Y4GcHoEHqCV8X+AsAnPZ9iC29IBAID1CDwAAMB6BB4AAGA9Ag8AALAegQcAAFiPwAMAAKxH4AEAANYj8AAAAOsReAAAgPUIPAAAwHoEHgAAYD0CDwAAsB6BBwAAWI/AAwAArNehrQcAtIVeD7/d1kMAAPwd8Q4PAACwHoEHAABYj8ADAACsxzU8+MHCeT3MnnnZYesbANqDcJ2jz7fzM+/wAAAA653T7/AsWrRICxYsUDAY1JAhQ/Tcc8/p8ssvb+th4e+Iu6kAAK3hnA08y5cvV25urp5//nmlpqbqmWeeUWZmpioqKhQXF9fWwwsbXuABAGh95+xHWgsXLtS0adN0++23a8CAAXr++ecVFRWlJUuWtPXQAADAeeacfIfn6NGjKi0tVX5+vrMtIiJC6enpKikpaXaf+vp61dfXO+u1tbWSpFAoFN7BtrKm+iNtPQQAAE4rXK+vx/s1xrRqv+dk4Pnf//1fNTY2Kj4+3rU9Pj5en3/+ebP7FBYWas6cOSdtT0pKCssYAQBoz6KfCW//hw4dUnR0dKv1d04GnrORn5+v3NxcZ72pqUkHDhxQjx495PF4JP01NSYlJemrr76S3+9vq6GeM5gPN+bDjflwYz7cmA835sPth8yHMUaHDh1SYmJiq47pnAw8sbGxioyMVHV1tWt7dXW1AoFAs/v4fD75fD7XtpiYmGZr/X4/T8gTMB9uzIcb8+HGfLgxH27Mh9vZzkdrvrNz3Dl50bLX69Xw4cO1du1aZ1tTU5PWrl2rtLS0NhwZAAA4H52T7/BIUm5urqZMmaIRI0bo8ssv1zPPPKPDhw/r9ttvb+uhAQCA88w5G3huueUW/eUvf9Hs2bMVDAZ12WWXadWqVSddyNwSPp9PTzzxxEkffbVXzIcb8+HGfLgxH27Mhxvz4XYuzofHtPZ9XwAAAOeYc/IaHgAAgNZE4AEAANYj8AAAAOsReAAAgPXOqcBTUFAgj8fjWvr37++0X3PNNSe133XXXa4+qqqqlJ2draioKMXFxWnWrFlqaGhw1axfv17Dhg2Tz+fTxRdfrKVLl540lkWLFqlXr17q1KmTUlNTtWnTJlf7d999p5ycHPXo0UMXXHCBxo4de9IXJbaGP//5z7r11lvVo0cPde7cWSkpKdqyZYvTbozR7NmzlZCQoM6dOys9PV07d+509XHgwAFNnDhRfr9fMTExmjp1qurq6lw15eXlGjlypDp16qSkpCTNnz//pLG88cYb6t+/vzp16qSUlBS98847rvYzGcsPdbr5uO222056jowZM8bVhy3z0atXr5Meq8fjUU5OjqQze47a9Pdyuvlob+ePxsZGPf744+rdu7c6d+6svn376sknn3T9PlF7On+cyXy0p/PHoUOHdP/99ys5OVmdO3fWlVdeqc2bN7fo+OfdXJhzyBNPPGEGDhxo9u7d6yx/+ctfnParr77aTJs2zdVeW1vrtDc0NJhBgwaZ9PR08z//8z/mnXfeMbGxsSY/P9+p+eKLL0xUVJTJzc01O3bsMM8995yJjIw0q1atcmpee+014/V6zZIlS8z27dvNtGnTTExMjKmurnZq7rrrLpOUlGTWrl1rtmzZYq644gpz5ZVXtup8HDhwwCQnJ5vbbrvNbNy40XzxxRfm3XffNbt27XJq5s2bZ6Kjo82KFSvMp59+am644QbTu3dv8+233zo1Y8aMMUOGDDEff/yxef/9983FF19sxo8f77TX1taa+Ph4M3HiRLNt2zbz6quvms6dO5t///d/d2o+/PBDExkZaebPn2927NhhHnvsMdOxY0ezdevWFo0l3PMxZcoUM2bMGNdz5MCBA65+bJmPffv2uR5nUVGRkWTee+89Y8zpn6O2/b2cbj7a2/njqaeeMj169DArV640lZWV5o033jAXXHCBefbZZ52a9nT+OJP5aE/nj5tvvtkMGDDAbNiwwezcudM88cQTxu/3m6+//vqMj3++zcU5F3iGDBlyyvarr77a3Hfffadsf+edd0xERIQJBoPOtsWLFxu/32/q6+uNMcY89NBDZuDAga79brnlFpOZmemsX3755SYnJ8dZb2xsNImJiaawsNAYY0xNTY3p2LGjeeONN5yazz77zEgyJSUlZ/RYz0ReXp656qqrTtne1NRkAoGAWbBggbOtpqbG+Hw+8+qrrxpjjNmxY4eRZDZv3uzU/PGPfzQej8f8+c9/NsYY89vf/tZ069bNmaPjx+7Xr5+zfvPNN5vs7GzX8VNTU82dd955xmP5oU43H8b89YR14403nrLdpvn4W/fdd5/p27evaWpqOqPnqG1/L3/rxPkwpv2dP7Kzs80dd9zh2nbTTTeZiRMnGmPa3/njdPNhTPs5fxw5csRERkaalStXurYPGzbMPProo9Y+N86pj7QkaefOnUpMTFSfPn00ceJEVVVVudqXLVum2NhYDRo0SPn5+Tpy5IjTVlJSopSUFNeXE2ZmZioUCmn79u1OTXp6uqvPzMxMlZSUSJKOHj2q0tJSV01ERITS09OdmtLSUh07dsxV079/f/Xs2dOpaQ2///3vNWLECP385z9XXFychg4dqv/4j/9w2isrKxUMBl3jiI6OVmpqqjOOkpISxcTEaMSIEU5Nenq6IiIitHHjRqdm1KhR8nq9rjmpqKjQwYMHnZrvm7czGUu45+O49evXKy4uTv369dPdd9+t/fv3O202zceJjh49qpdffll33HGHPB7PGT1Hbft7OdHfzsdx7en8ceWVV2rt2rX605/+JEn69NNP9cEHHygrK0tS+zt/nG4+jmsP54+GhgY1NjaqU6dOru2dO3fWBx98YO1z45z6puXU1FQtXbpU/fr10969ezVnzhyNHDlS27ZtU9euXTVhwgQlJycrMTFR5eXlysvLU0VFhd58801JUjAYPOmbmI+vB4PB760JhUL69ttvdfDgQTU2NjZb8/nnnzt9eL3ek36cND4+3jlOa/jiiy+0ePFi5ebm6pFHHtHmzZt17733yuv1asqUKc6xmhvriY83Li7O1d6hQwd1797dVdO7d++T+jje1q1bt1PO24l9nG4sP9Tp5kOSxowZo5tuukm9e/fW7t279cgjjygrK0slJSWKjIy0aj5OtGLFCtXU1Oi2225zjn+656htfy8n+tv5kNTuzh8PP/ywQqGQ+vfvr8jISDU2Nuqpp57SxIkTXY+pvZw/TjcfUvs5f3Tt2lVpaWl68skndemllyo+Pl6vvvqqSkpKdPHFF1v73DinAs+JSXvw4MFKTU1VcnKyXn/9dU2dOlXTp0932lNSUpSQkKDRo0dr9+7d6tu3b1sMOayampo0YsQIPf3005KkoUOHatu2bXr++eedF/j25EzmY9y4cU59SkqKBg8erL59+2r9+vUaPXp0m4z77+HFF19UVlaWEhMT23oo54Tm5qO9nT9ef/11LVu2TK+88ooGDhyosrIy3X///UpMTGyX548zmY/2dP747//+b91xxx266KKLFBkZqWHDhmn8+PEqLS1t66GFzTn3kdaJYmJidMkll2jXrl3NtqempkqS0x4IBE660+H4eiAQ+N4av9+vzp07KzY2VpGRkc3WnNjH0aNHVVNTc8qa1pCQkKABAwa4tl166aXOx3zHj3W6se7bt8/V3tDQoAMHDpx2Tk48xqlqTmw/3Vh+qNPNR3P69Omj2NhY13PElvk47ssvv9SaNWv0i1/8wtl2Js9R2/5ejmtuPppj+/lj1qxZevjhhzVu3DilpKRo0qRJmjlzpgoLC12Pqb2cP043H82x+fzRt29fbdiwQXV1dfrqq6+0adMmHTt2TH369LH2uXFOB566ujrt3r1bCQkJzbaXlZVJktOelpamrVu3uv4jFBUVye/3Oy+UaWlpWrt2raufoqIipaWlSZK8Xq+GDx/uqmlqatLatWudmuHDh6tjx46umoqKClVVVTk1reGnP/2pKioqXNv+9Kc/KTk5WZLUu3dvBQIB1zhCoZA2btzojCMtLU01NTWu1L5u3To1NTU5J/y0tDQVFxfr2LFjTk1RUZH69eunbt26OTXfN29nMpYf6nTz0Zyvv/5a+/fvdz1HbJmP41566SXFxcUpOzvb2XYmz1Hb/l6Oa24+mmP7+ePIkSOKiHCf4iMjI9XU1CSp/Z0/TjcfzWkP548uXbooISFBBw8e1Lvvvqsbb7zR3udGiy5xDrMHHnjArF+/3lRWVpoPP/zQpKenm9jYWLNv3z6za9cuM3fuXLNlyxZTWVlp3nrrLdOnTx8zatQoZ//jt5VmZGSYsrIys2rVKnPhhRc2e1vprFmzzGeffWYWLVrU7G2lPp/PLF261OzYscNMnz7dxMTEuO7euOuuu0zPnj3NunXrzJYtW0xaWppJS0tr1fnYtGmT6dChg3nqqafMzp07zbJly0xUVJR5+eWXnZp58+aZmJgY89Zbb5ny8nJz4403Nnvr4NChQ83GjRvNBx98YH784x+7bh2sqakx8fHxZtKkSWbbtm3mtddeM1FRUSfdOtihQwfzq1/9ynz22WfmiSeeaPbWwdONJZzzcejQIfPggw+akpISU1lZadasWWOGDRtmfvzjH5vvvvvOuvkw5q93APXs2dPk5eWd1Ha656htfy/fNx/t8fwxZcoUc9FFFzm3Yb/55psmNjbWPPTQQ05Nezp/nG4+2tv5Y9WqVeaPf/yj+eKLL8zq1avNkCFDTGpqqjl69OgZH/98m4tzKvDccsstJiEhwXi9XnPRRReZW265xfmOlaqqKjNq1CjTvXt34/P5zMUXX2xmzZrl+h4NY4zZs2ePycrKMp07dzaxsbHmgQceMMeOHXPVvPfee+ayyy4zXq/X9OnTx7z00ksnjeW5554zPXv2NF6v11x++eXm448/drV/++235pe//KXp1q2biYqKMv/0T/9k9u7d27oTYoz5wx/+YAYNGmR8Pp/p37+/eeGFF1ztTU1N5vHHHzfx8fHG5/OZ0aNHm4qKClfN/v37zfjx480FF1xg/H6/uf32282hQ4dcNZ9++qm56qqrjM/nMxdddJGZN2/eSWN5/fXXzSWXXGK8Xq8ZOHCgefvtt1s8lh/q++bjyJEjJiMjw1x44YWmY8eOJjk52UybNs31QmOMXfPx7rvvGknN9nsmz1Hb/l5ONR/t8fwRCoXMfffdZ3r27Gk6depk+vTpYx599FHXLcLt6fxxuvlob+eP5cuXmz59+hiv12sCgYDJyckxNTU1LTr++TYXHmNO+JpJAAAAC53T1/AAAAC0BgIPAACwHoEHAABYj8ADAACsR+ABAADWI/AAAADrEXgAAID1CDwAAMB6BB4AAGA9Ag8AALAegQcAAFiPwAMAAKz3f4+YaHdwuMnqAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#savedHDunitList = [HDunitList[t].copy() for t in range(nHDs) ]  #safekeeping\n",
    "HDunitList = [savedHDunitList[t].copy() for t in range(nHDs) ]   #restart\n",
    "HDvPop = [0 for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins=20)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "id": "551454fb-d57c-466f-8b31-39ccb2a728de",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "here are the HD centers for 150 cantFill HDs with border or big enclaves\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"here are the HD centers for\",len(cantFill),\"cantFill HDs with border or big enclaves\")\n",
    "for u in borderUnits:\n",
    "    plotPoly(unitGeom[u])\n",
    "for t in cantFill:\n",
    "    plotPoly(hdCP[t].buffer(0.1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "id": "5269a224-4a97-417c-99af-6a98df0087ae",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 801\n",
      "working on avg unit-to-HDcp dist for HD 1601\n",
      "working on avg unit-to-HDcp dist for HD 2403\n",
      "working on avg unit-to-HDcp dist for HD 3203\n",
      "working on avg unit-to-HDcp dist for HD 4004\n",
      "all unit-toHDcp distances computed\n"
     ]
    }
   ],
   "source": [
    "barredJettisonSet = set([2725, 2726, 2727, 2728] )  #lock in the clusters  #update this for each state\n",
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "print(\"all unit-toHDcp distances computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "id": "6e2e44bd-a084-42f6-b533-5dc6d21912a9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this code will solve large enclaves so HD and complement are contiguous for 150 HDs\n",
      "working on HD 63 cantFill 0 of 150 .Time is now 0\n",
      "working on HD 1415 cantFill 20 of 150 .Time is now 1\n",
      "working on HD 3918 cantFill 40 of 150 .Time is now 1\n",
      "working on HD 565 cantFill 60 of 150 .Time is now 2\n",
      "working on HD 1008 cantFill 80 of 150 .Time is now 4\n",
      "working on HD 1442 cantFill 100 of 150 .Time is now 5\n",
      "working on HD 1999 cantFill 120 of 150 .Time is now 6\n",
      "working on HD 3986 cantFill 140 of 150 .Time is now 6\n",
      "after the MustFree code run, we have the following for cluster usage\n",
      "current avg use and its sd are 1.02277 0.13227\n",
      "CCB cluster 0 = unit 2725 with pop 314005.0 now has use of 0.9978666410583948\n",
      "CCB cluster 1 = unit 2726 with pop 148064.0 now has use of 0.9962796771537515\n",
      "CCB cluster 2 = unit 2727 with pop 216736.0 now has use of 1.0021382656320768\n",
      "CCB cluster 3 = unit 2728 with pop 65226.0 now has use of 1.001220013549454\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS IS THE MUSTFREE CODE - for high-pop HDs with map-border enclaves, can't fill; \n",
    "#  must jettison some inHD map-boundary units to connect the enclave to the larger complement\n",
    "#For each HD to be triaged, define the list(s) of contiguous enclave units that are on the map boundary, \n",
    "#  and the in-HD map-boundary segments.  ID which in-HD MBS's adjoin one vs. two enclaves.\n",
    "#     Fill all internal enclaves, and all boundary enclaves < 0.05 aDP.\n",
    "#   Then each loop, look for boundary enclaves that can be filled without overpopping.\n",
    "#     If none, pick the 1/2 has-1-boundary-enclave-neighbor that is least painful to jettison to free an enclave.\n",
    "#       (Jettison score based on pop-to-Free and distance from HDcP)\n",
    "#         Update HDpop, HDlist, and enclave & HD-boundary associations, then re-loop\n",
    "# Later, we will swell-fill to square up pop (w/ checkEnclave) biasing toward close-to-hdCP, underused\n",
    "borderSet = set(borderUnits)\n",
    "debug, debugPlot = False, False\n",
    "startTime = time.time()  #takes about 1.5sec per HD triage\n",
    "clusterJettisonBoost = 3.  #this discourages jettisoning of underused clusters\n",
    "print(\"this code will solve large enclaves so HD and complement are contiguous for\",len(cantFill),\"HDs\")\n",
    "nEnclavesPerHD = [0 for t in range(nHDs)]\n",
    "HDenclaveLists = [list() for t in range(nHDs)]\n",
    "for iii,t in enumerate(cantFill):\n",
    "    if iii %20 == 0:\n",
    "        print(\"working on HD\",t,\"cantFill\",iii,\"of\",len(cantFill),\".Time is now\",int(time.time() - startTime) )\n",
    "    shedUs = list()    \n",
    "    enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "    nEnclavesPerHD[t] = len(enclaveLists)\n",
    "    HDenclaveLists[t] = enclaveLists.copy()\n",
    "    if debug:\n",
    "        print(\"pre-adjust HDpop for HD\",t,\"is\",HDvPop[t],\"I found\",len(enclaveLists),\"TOTAL enclaves\")\n",
    "    internalEnclaves, edgeEnclaves, combinedEnclBorderList = list(), list(), list()\n",
    "    for jjj, eL in enumerate(enclaveLists.copy() ):\n",
    "        enclaveBorderList = list ( set(eL).intersection(borderSet) )\n",
    "        if debug:\n",
    "            print(\"In enclave\",jjj,\"I found\",len(enclaveBorderList),\"units that were enclaved and are in the map borderSet\")\n",
    "        combinedEnclBorderList += enclaveBorderList\n",
    "        ePop = np.sum( [unitPop[u] for u in eL] )\n",
    "        if len(enclaveBorderList) == 0 or ePop < 0.05 * aDP:  #internal or small enclave.  Fill it\n",
    "            if ePop > 0:  #in a prev treatment, could be an empty (surrounded) unit that we don't care about\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += ePop\n",
    "            internalEnclaves.append(eL)\n",
    "        else:\n",
    "            edgeEnclaves.append(eL)\n",
    "    if debug:\n",
    "        print(\"Of these\",len(internalEnclaves),\"were internal or small, so I filled them, leaving\",\n",
    "              len(edgeEnclaves),\"non-small border = edge enclaves\" )\n",
    "    if debugPlot:\n",
    "        print(\"Here is the original HD, internal enclaves ('x') and non-small border enclaves by enclave no\")\n",
    "        plotPoly(hdCP[t].buffer(0.3))\n",
    "        for u in HDunitList[t]:\n",
    "            if unitPop[u] > 0:\n",
    "                plotPoly(unitGeom[u],0.2)\n",
    "        for L in internalEnclaves:\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u],1.5)\n",
    "                    plotCenter(\"x\",unitCP[u],8)\n",
    "        for L in edgeEnclaves: #############\n",
    "            for u in L:\n",
    "                if unitPop[u] > 0:\n",
    "                    plotPoly(unitGeom[u])\n",
    "                    #plotCenter(\"e\",unitCP[u],8)\n",
    "        #plotPoly(MAP,0.4)\n",
    "        #plt.show()\n",
    "    enclaveLists, combinedEnclBorderSet = list(), set(combinedEnclBorderList)\n",
    "    if len(edgeEnclaves) > 0:\n",
    "        # Now, we order by chain connectivity of HD and enclave sublists to be H0-E0-H1-E1 ... En-Hn+1\n",
    "        nonHDborderSet = borderSet.difference(  set(HDunitList[t]) )\n",
    "        nonHDlongBorderSet = nonHDborderSet.difference(combinedEnclBorderSet) #long=non HD boundary excluding enclaves\n",
    "        remainingEnclBorderSet = combinedEnclBorderSet.copy()\n",
    "        remainingHDborderSet =   borderSet.intersection(set(HDunitList[t]) )\n",
    "        #Now find the \"HDender\" unit which borders the non-enclave nonHD boundary, then find opp end of this HD bdry piece\n",
    "        HDender = list(set(getAdjoiners(nonHDlongBorderSet,unitNbrs)).intersection(remainingHDborderSet) )[0]\n",
    "        firstHDborderSet = getContigFromStarter(HDender,remainingHDborderSet,unitNbrs)\n",
    "        HDstarter = list(set(getAdjoiners(remainingEnclBorderSet,unitNbrs)).intersection(firstHDborderSet))[0]\n",
    "        HDborderSublists = [ list(firstHDborderSet) ]\n",
    "        unused = [1 for eL in edgeEnclaves]\n",
    "        eLadjoiners = [getAdjoiners(eL,unitNbrs) for eL in edgeEnclaves ]\n",
    "        for j in range(len(edgeEnclaves)): #find the enclave with the most HDstarter neighbors (at least 1)\n",
    "            found = False\n",
    "            for i,eL in enumerate(edgeEnclaves):\n",
    "                if unused[i] == 1:\n",
    "                    HDadjSet = set(HDborderSublists[j]).intersection(set(eLadjoiners[i]))\n",
    "                    if len(HDadjSet) > 0:\n",
    "                        unused[i] = 0\n",
    "                        eNo = i\n",
    "                        found = True\n",
    "                        remainingEnclBorderSet = remainingEnclBorderSet.difference(set(edgeEnclaves[eNo]) )\n",
    "                        enclaveLists.append(edgeEnclaves[eNo])\n",
    "                        remainingHDborderSet = remainingHDborderSet.difference(set(HDborderSublists[j]) )\n",
    "                        HDstarter = list(set(eLadjoiners[i]).intersection(remainingHDborderSet))[0]       \n",
    "                        HDborderSublists.append(getContigFromStarter(HDstarter,remainingHDborderSet,unitNbrs) )\n",
    "                        break\n",
    "                if found:\n",
    "                    break\n",
    "\n",
    "        enclavePops = [np.sum([unitPop[u] for u in L]) for L in enclaveLists]\n",
    "        #print(\"prior to adjustments, border enclavePops are\",enclavePops)         \n",
    "\n",
    "        nHDBS, nEnclaves = len(HDborderSublists), len(enclaveLists)\n",
    "        popToFree, freeingCounties, freeingUnits = [0. for n in range(nHDBS)], [list() for n in range(nHDBS) \n",
    "                                                                               ],[list() for n in range(nHDBS)]\n",
    "        for j,L in enumerate(HDborderSublists):\n",
    "            for u in L:\n",
    "                if int(allUnits[u]) == allUnits[u]:  #this border unit is a vtd\n",
    "                    c = countyNo[parentVTDno[allUnits[u]]]   #countyNo[allUnits[u]]\n",
    "                    if c not in freeingCounties[j]:\n",
    "                        if countyPop[c] < 0.1 * aDP:  #plan to add all in-county pop\n",
    "                            freeingCounties[j].append(c)\n",
    "                        else:\n",
    "                            popToFree[j] += unitPop[u]\n",
    "                            freeingUnits[j].append(u)\n",
    "                else: #border unit is a full county or cluster, or in a dense county.  Add the whole unit pop\n",
    "                    popToFree[j] += unitPop[u]\n",
    "                    freeingUnits[j].append(u)\n",
    "            for c in freeingCounties[j]:  #include ALL in-HD pop from each non-unit border county, not just its border units\n",
    "                #plotPoly(countyGeom[c],0.1)\n",
    "                for u in countyUnitList[c]:\n",
    "                    if u in HDunitList[t]:\n",
    "                        popToFree[j] += unitPop[u]\n",
    "                        freeingUnits[j].append(u)\n",
    "        freeingCP = [ getHDcp(  unitCP, unitPop, L) for L in freeingUnits ]\n",
    "        freeingScore = [ pTF/aDP - 0.5*freeingCP[j].distance(hdCP[t]) / avgDist[t] for j,pTF in enumerate(popToFree) ]\n",
    "        for j, fU in enumerate(freeingUnits):  #in above 0.5 is a fudgy\n",
    "            if len(barredJettisonSet.intersection(set(fU)) ) > 0: #has a cluster we want to hold onto\n",
    "                freeingScore[j] += clusterJettisonBoost #  ..so increase its score (make it harder to drop)\n",
    "        if debugPlot:\n",
    "            print(\"plotting the freeing units with negative numbers for each freeing group\")\n",
    "            for j,L in enumerate(freeingUnits):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        #plotPoly(unitGeom[u],0.5)\n",
    "                        plotCenter(\"-\"+str(j),unitGeom[u],6)\n",
    "                        pass\n",
    "            print(\"plotting the enclaveLists, with + numbers for each enclave\")\n",
    "            for j,L in enumerate(enclaveLists):\n",
    "                for u in L:\n",
    "                    if unitPop[u] > 0:\n",
    "                        plotPoly(unitGeom[u])\n",
    "                        plotCenter(j,unitCP[u],8)\n",
    "                        pass\n",
    "    \n",
    "    while len(enclaveLists) > 0:\n",
    "        if HDvPop[t] + np.min(enclavePops) < 1.05*aDP or np.min(enclavePops) < 0.05 * aDP:  #fill the smallest enclave\n",
    "            eNo = enclavePops.index(np.min(enclavePops))\n",
    "            HDunitList[t] += enclaveLists[eNo]\n",
    "            HDvPop[t] += enclavePops[eNo]\n",
    "            #print(t,\"=t. Absorbing enclave\",eNo,\"with pop\",enclavePops[eNo],\"HD total pop now\",int(HDfreePop[t]) )\n",
    "            enclaveBUs = list(set(enclaveLists[eNo]).intersection(set(borderUnits)) )\n",
    "            enclaveBpop = np.sum([unitPop[u] for u in enclaveBUs])\n",
    "            sNo, dropped_sNo = eNo, eNo+1\n",
    "            freeingScore[sNo] += freeingScore[sNo+1]+enclaveBpop/aDP\n",
    "            freeingUnits[sNo] += freeingUnits[sNo+1]+enclaveBUs\n",
    "            popToFree[sNo]    +=    popToFree[sNo+1]+enclaveBpop\n",
    "        else: #jettison one of the two end HD border lists; pick the less painful path to freedom\n",
    "            distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "            starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "            eNo, dropped_sNo = 0,0\n",
    "            if starterU not in freeingUnits[-1]:  #we can't drop the home unit, even to save an underused corner\n",
    "                if freeingScore[-1] < freeingScore[0] or starterU in freeingUnits[0]:\n",
    "                    eNo, dropped_sNo = len(enclaveLists)-1,len(enclaveLists)\n",
    "            barredIncluded0 = barredJettisonSet.intersection(set(freeingUnits[0]))\n",
    "            barredIncluded_1 = barredJettisonSet.intersection(set(freeingUnits[-1]))\n",
    "            #if len(barredIncluded0.union(barredIncluded_1)) > 0:\n",
    "            #    print(\"We are considering dropping an end unit to free from t\",t,\". Chosen, beg, end, scores are\")\n",
    "            #    print(dropped_sNo,barredIncluded0, barredIncluded_1, freeingScore[0], freeingScore[-1])\n",
    "            HDunitList[t] = list( set(HDunitList[t]).difference(set(freeingUnits[dropped_sNo]) ) )\n",
    "            HDvPop[t] -= popToFree[dropped_sNo]\n",
    "            #print(t,\"= t. Jettisoning HDborder\",dropped_sNo,\"with popToFree\",popToFree[dropped_sNo] )\n",
    "        del enclaveLists[eNo]\n",
    "        del enclavePops[eNo]\n",
    "        if debug:\n",
    "            print(t,\"= t. Now we have\",len(enclaveLists),\"left trapped.  Picked eNo, freeScores were\", eNo,freeingScore)\n",
    "        del freeingScore[dropped_sNo]\n",
    "        del freeingUnits[dropped_sNo]\n",
    "        del popToFree   [dropped_sNo] \n",
    "\n",
    "    #plotPoly(MAP,0.4)\n",
    "    if debugPlot:\n",
    "        plt.show()    \n",
    "        \n",
    "unitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t]*nDistricts\n",
    "print(\"after the MustFree code run, we have the following for cluster usage\")\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "id": "ca9ce3cb-c150-4f39-ae55-f781d39d7f57",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "postMustFreeUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "id": "c32dd108-073b-48aa-99ce-fea50c8d023c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist([HDvPop[t] for t in popHDlist] )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "id": "f58fe2d0-3c62-412f-8984-ff5d67ea9b10",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "After above work, re-classification of contiguity problems?\n",
      "working on HD 0\n",
      "working on HD 500\n",
      "working on HD 1000\n",
      "working on HD 1500\n",
      "working on HD 2000\n",
      "working on HD 2500\n",
      "working on HD 3000\n",
      "working on HD 3500\n",
      "working on HD 4000\n",
      "out of 4106 total HDs, there were 3886 1 140 79 HDs that were clean, discontig only, enclave-only, both problems after triage\n"
     ]
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"After above work, re-classification of contiguity problems?\")\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "id": "1ef683a2-4429-4a91-b1ea-a9b0950dea22",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on current HD diam for HD number 0\n",
      "working on current HD diam for HD number 801\n",
      "working on current HD diam for HD number 1601\n",
      "working on current HD diam for HD number 2403\n",
      "working on current HD diam for HD number 3203\n",
      "working on current HD diam for HD number 4004\n",
      "here is the histogram of HD diameter = sqrt(area)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "HDdiam = [0. for t in range(nHDs)]\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on current HD diam for HD number\",t)\n",
    "    HDdiam[t] = (HDpoly[t].intersection(MAP) ).area ** 0.5\n",
    "plt.hist([HDdiam[t] for t in popHDlist])\n",
    "print(\"here is the histogram of HD diameter = sqrt(area)\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "id": "45e3c17c-8c16-4bc5-b7fc-25b9250ed11a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we will regrow all disco'd HDs off by more than  35665 but less than 178327\n",
      "... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\n",
      "This is a total of 80 HDs to triage in this block\n",
      "working on swell-filling discontig HD 453 our 1 th HD we think we can swell out of 80\n",
      "working on swell-filling discontig HD 1759 our 41 th HD we think we can swell out of 80\n",
      "we partially regrew 56 HDs, leaving 164 to regrow from scratch\n"
     ]
    }
   ],
   "source": [
    "### THIS IS THE CANSWELL CODE\n",
    "print(\"Here, we will regrow all disco'd HDs off by more than \",int(aDP-minPostFixPop),\"but less than\",int(0.25*aDP) )\n",
    "print(\"... from the contiguous block that contains the hdCP (not full regrowth).  We will swell out, avoiding enclaves\")\n",
    "HDnAddedUnits = [0 for t in range(nHDs)]\n",
    "maxGap = 0.9 * np.median(unitPop)  #set a reasonable gap prior to picking the last block\n",
    "HDdiam = [HDpoly[t].area ** 0.5 for t in range(nHDs) ] #in case not defined before\n",
    "badDiscoList = list()\n",
    "nCanSwell = 0\n",
    "triageList = discontigOnly + bothProblems\n",
    "print(\"This is a total of\",len(triageList),\"HDs to triage in this block\")\n",
    " \n",
    "for i,t in enumerate(triageList): #canSwell\n",
    "    if i%40 == 0:\n",
    "        print(\"working on swell-filling discontig HD\",t,\"our\",i+1,\"th HD we think we can swell out of\",len(triageList) )\n",
    "    distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "    starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = getContigFromStarter(starterU, HDunitList[t], unitNbrs)\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    if contigPop < 0.50 * aDP or contigPop > 2.*aDP - minPostFixPop:  #formerly < 0.75 aDP\n",
    "        badDiscoList.append(t)\n",
    "    else: #rebuild from this big piece\n",
    "        nCanSwell +=1\n",
    "        gap = aDP - contigPop\n",
    "        origGap = gap\n",
    "        currList, addedList = contigUs.copy(), list()\n",
    "        adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "        nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "        nearHDscore = [ (unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] for uu in adjoiners ] \n",
    "        stillGoing = True\n",
    "\n",
    "        while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "            while i < len(nearHDscore) and notYetPicked:        \n",
    "                listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "                canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "                if canAdd:\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't add any more units without creating an enclave\n",
    "            else: #we selected the best unit to add legally\n",
    "                gap -= unitPop[unitNoToAdd]\n",
    "                addedList.append(unitNoToAdd)  #so add it to our growing HD ...\n",
    "                currList.append( unitNoToAdd)\n",
    "                for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                    if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append((unitUse[uu] - 1.) + 0.5*(unitCP[uu].distance(\n",
    "                            HDpoly[t]) + unitCP[uu].distance(hdCP[t]) ) / HDdiam[t] )\n",
    "                del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                for i, uu in enumerate(nearHDlist.copy()):\n",
    "                    if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                        del nearHDscore[nearHDlist.index(uu)]\n",
    "                        del nearHDlist[ nearHDlist.index(uu)]\n",
    "        for u in addedList:\n",
    "            unitUse[u] += HDweight[t] * nDistricts\n",
    "        for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "            unitUse[u] -= HDweight[t] * nDistricts       \n",
    "        HDunitList[t] = contigUs + addedList\n",
    "        HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "        HDnAddedUnits[t] = len(addedList)\n",
    "    \n",
    "badDiscoList += enclaveOnly\n",
    "print(\"we partially regrew\",nCanSwell,\"HDs, leaving\",len(badDiscoList),\"to regrow from scratch\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "id": "f57325dd-523c-466a-80cb-8e10b739b4ac",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "previous avg use and its sd are 1.02277 0.13227\n",
      "defining and displaying current unit use after above manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01877 0.1316\n",
      "CCB cluster 0 = unit 2725 with pop 314005.0 now has use of 0.9821484084623385\n",
      "CCB cluster 1 = unit 2726 with pop 148064.0 now has use of 0.9862518036468314\n",
      "CCB cluster 2 = unit 2727 with pop 216736.0 now has use of 0.9410177247185143\n",
      "CCB cluster 3 = unit 2728 with pop 65226.0 now has use of 1.0002526945616483\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"previous avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after above manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "\n",
    "for u, unitNo in enumerate(allUnits):\n",
    "    if unitNo % 1 == 0.25:\n",
    "        print(\"CCB cluster\",int(unitNo),\"= unit\",u,\"with pop\",unitPop[u],\"now has use of\",unitUse[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "id": "0ce918e1-0d30-4930-9fb8-0769d793683c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "quick classification: who has contiguity problems?\n",
      "working on HD 0 time is now 0\n",
      "working on HD 1001 time is now 19\n",
      "working on HD 2003 time is now 38\n",
      "working on HD 3003 time is now 48\n",
      "working on HD 4004 time is now 57\n",
      "out of 4106 total HDs, there were 4082.0 contiguous and 3900.0 complement-contiguous HDs\n",
      "24 HDs had both discontiguity problems, while enclave-only = 182 and discontig only= 0\n",
      "here are the histograms of the small piece and enclave list lengths, total no = 24 182\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And here are the small-HD-piece and small-enclave pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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Ddffdd2vRokVOr1m4cKEGDhyogIAAlZeXKzk5WUFBQfr888+1adMmBQYGqn///m4JCpMnT9agQYO0bds2paamavDgwcrNzZUklZaWKjk5WU2bNtXXX3+tpUuXavXq1RozZozTGGvWrFFubq7Wr1+vxYsX64MPPlB6errLa20QTANUXFxsJJni4mLXD75lgTFpwef/CQD1wOnTp83u3bvN6dOn/3/joa3n/1t1aOu1KaKW+ztz5owJCAgwX375pdP24cOHmyFDhhhjjFm3bp2RZFavXu1oX7FihZHkONaEhASTmpp6yf20bt3avPHGG5dsX7p0qWnWrJljfdmyZSYwMNCUlpYaY86/n/j5+ZnPPvvMGGPMu+++azp27GgqKysdrykrKzP+/v7mH//4xxWPOy0tzcTFxV2xnzHGSDKjRo1y2hYfH28ef/xxY4wxf/7zn03Tpk1NSUmJo33FihXGw8PDFBYWGmOMGTp0qAkLC3McjzHGzJ071wQGBppz587VqA5Xq/b39f+49f3bGMOZGgCAy+Xn5+vUqVP62c9+psDAQMfyzjvvaO/evU59u3Xr5vg5KipKknTs2DFJUk5OjhITE2u839WrVysxMVEtW7ZUUFCQHnnkER0/ftxxaWnAgAHy9vbWRx99JEn6n//5HwUHByspKUmStG3bNuXn5ysoKMhRc1hYmM6cOVOlbldISEiosn7hTE1ubq7i4uLUpEkTR/stt9yiyspKp0t0cXFxCggIcBqjpKREBw4ccHm99R03CgMAXO7CfR8rVqxQy5Ytndp8fX2d1r29vR0/22w2Sefvx5Ekf3//Gu/zu+++0913363HH39cL730ksLCwvTFF19o+PDhOnv2rAICAuTj46MHH3xQixYt0uDBg7Vo0SI9/PDD8vLyctTds2dPLVy4sMr4LVq0qHEtqBucqQEAuNwNN9wgX19f7d+/X+3atXNaYmJq/vRUt27dtGbNmhr1zc7OVmVlpV5//XXdfPPN6tChgw4fPlylX2pqqlauXKldu3Zp7dq1Sk1NdbT16NFDe/bsUXh4eJW6Q0JCalx3TW3evLnKeufOnSVJnTt31rZt21RaWupo37Rpkzw8PNSxY0fHtm3btun06dNOYwQGBtZqnq2CUAMAcLmgoCD99re/1bhx4/T2229r7969+uabbzR79my9/fbbNR4nLS1NixcvVlpamnJzc7Vjxw698sor1fZt166dysvLNXv2bH377bd69913NW/evCr9+vbtq8jISKWmpio2Nlbx8fGOttTUVDVv3lz33XefPv/8cxUUFGj9+vV66qmndPDgwUvWmZ+fr5ycHBUWFur06dPKyclRTk7OFW8uXrp0qd566y3961//Ulpamr766ivHjcCpqany8/PT0KFDtXPnTq1bt05PPvmkHnnkEUVERDjGOHv2rIYPH67du3fr008/VVpamsaMGSMPj8b3Fs/lJwBoyP79r3q7n9///vdq0aKFMjIy9O233yo0NFQ9evTQ7373uxqP0a9fPy1dulS///3vNW3aNAUHB6tv377V9o2Li9OMGTP0yiuvaNKkSerbt68yMjL0q1/9yqmfzWbTkCFD9Oqrr2rKlClObQEBAdq4caMmTpyoBx54QCdPnlTLli2VmJio4ODgS9b5m9/8xumpru7du0uSCgoK1KZNm0u+Lj09XUuWLNETTzyhqKgoLV68WDfccIOjln/84x96+umn1bt3bwUEBGjQoEGaMWOG0xiJiYlq3769+vbtq7KyMg0ZMkRTp0695D6tzGaMMXVdRG3Z7XaFhISouLj4sr9kVyX7benjp6R7Zkk9h7p2bAC4CmfOnFFBQYFiY2Pl5+d3fiOfKNzg2Ww2LVu2TAMHDrzqMR599FEVFRVp+fLlLqvrx6r29/X/uPX9W5ypAYCGKTTmfMBo5N/9BFyMUAMADVVoDCEDuAihBgCAOuCKuz8WLFjw4wuxkMZ3azQAALAkQg0AALAEQg0ANBAN8GFVNEJ1+XtKqAGAes7T01OS3PIt0YCrXfierYu//uJa4UZhAKjnvLy8FBAQoO+//17e3t6N8pNiUf8ZY3Tq1CkdO3ZMoaGhjjB+LRFqAKCes9lsioqKUkFBgfbt21fX5QCXFRoaqsjIyDrZN6EGABoAHx8ftW/fnktQqNe8vb3r5AzNBYQaAGggPDw8qnzsPID/x4VZAABgCYQaAABgCYQaAABgCYQaAABgCYQaAABgCYQaAABgCYQaAABgCbUONRs3btQ999yj6Oho2Ww2LV++3Kn90Ucflc1mc1r69+/v1OfEiRNKTU1VcHCwQkNDNXz4cJWUlPyoAwEAAI1brUNNaWmp4uLiNGfOnEv26d+/v44cOeJYFi9e7NSempqqXbt2adWqVfrkk0+0ceNGjRw5svbVAwAA/J9af6JwSkqKUlJSLtvH19f3kt/7kJubq5UrV+rrr79Wr169JEmzZ8/WgAED9Nprryk6Orq2JQEAALjnnpr169crPDxcHTt21OOPP67jx4872jIzMxUaGuoINJKUlJQkDw8PZWVluaMcAADQCLj8u5/69++vBx54QLGxsdq7d69+97vfKSUlRZmZmfL09FRhYaHCw8Odi/DyUlhYmAoLC6sds6ysTGVlZY51u93u6rIBAEAD5/JQM3jwYMfPXbt2Vbdu3XT99ddr/fr1SkxMvKoxMzIylJ6e7qoSAQCABbn9ke62bduqefPmys/PlyRFRkbq2LFjTn0qKip04sSJS96HM2nSJBUXFzuWAwcOuLtsAADQwLg91Bw8eFDHjx9XVFSUJCkhIUFFRUXKzs529Fm7dq0qKysVHx9f7Ri+vr4KDg52WgAAAC5W68tPJSUljrMuklRQUKCcnByFhYUpLCxM6enpGjRokCIjI7V37149++yzateunZKTkyVJnTt3Vv/+/TVixAjNmzdP5eXlGjNmjAYPHsyTTwAA4KrV+kzNli1b1L17d3Xv3l2SNH78eHXv3l1TpkyRp6entm/frnvvvVcdOnTQ8OHD1bNnT33++efy9fV1jLFw4UJ16tRJiYmJGjBggG699Vb9+c9/dt1RAQCARqfWZ2r69esnY8wl2//xj39ccYywsDAtWrSotrsGAAC4JL77CQAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWAKhBgAAWEKtQ83GjRt1zz33KDo6WjabTcuXL3e0lZeXa+LEieratauaNGmi6Oho/epXv9Lhw4edxmjTpo1sNpvTMm3atB99MAAAoPGqdagpLS1VXFyc5syZU6Xt1KlT+uabbzR58mR98803+uCDD5SXl6d77723St8XX3xRR44ccSxPPvnk1R0BAACAJK/aviAlJUUpKSnVtoWEhGjVqlVO2/7rv/5Lffr00f79+9WqVSvH9qCgIEVGRtZ29wAAANVy+z01xcXFstlsCg0Nddo+bdo0NWvWTN27d9f06dNVUVFxyTHKyspkt9udFgAAgIvV+kxNbZw5c0YTJ07UkCFDFBwc7Nj+1FNPqUePHgoLC9OXX36pSZMm6ciRI5oxY0a142RkZCg9Pd2dpQIAgAbObaGmvLxcDz30kIwxmjt3rlPb+PHjHT9369ZNPj4+euyxx5SRkSFfX98qY02aNMnpNXa7XTExMe4qHQAANEBuCTUXAs2+ffu0du1ap7M01YmPj1dFRYW+++47dezYsUq7r69vtWEHAADgApeHmguBZs+ePVq3bp2aNWt2xdfk5OTIw8ND4eHhri4HAAA0ErUONSUlJcrPz3esFxQUKCcnR2FhYYqKitKDDz6ob775Rp988onOnTunwsJCSVJYWJh8fHyUmZmprKws3XHHHQoKClJmZqbGjRunX/7yl2ratKnrjgwAADQqtQ41W7Zs0R133OFYv3Cvy9ChQzV16lR99NFHkqSbbrrJ6XXr1q1Tv3795OvrqyVLlmjq1KkqKytTbGysxo0b53TPDAAAQG3VOtT069dPxphLtl+uTZJ69OihzZs313a3AAAAl8V3PwEAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEsg1AAAAEuodajZuHGj7rnnHkVHR8tms2n58uVO7cYYTZkyRVFRUfL391dSUpL27Nnj1OfEiRNKTU1VcHCwQkNDNXz4cJWUlPyoAwEAAI1brUNNaWmp4uLiNGfOnGrbX331Vc2aNUvz5s1TVlaWmjRpouTkZJ05c8bRJzU1Vbt27dKqVav0ySefaOPGjRo5cuTVHwUAAGj0vGr7gpSUFKWkpFTbZozRzJkz9cILL+i+++6TJL3zzjuKiIjQ8uXLNXjwYOXm5mrlypX6+uuv1atXL0nS7NmzNWDAAL322muKjo7+EYcDAAAaK5feU1NQUKDCwkIlJSU5toWEhCg+Pl6ZmZmSpMzMTIWGhjoCjSQlJSXJw8NDWVlZ1Y5bVlYmu93utAAAAFzMpaGmsLBQkhQREeG0PSIiwtFWWFio8PBwp3YvLy+FhYU5+vynjIwMhYSEOJaYmBhXlg0AACygQTz9NGnSJBUXFzuWAwcO1HVJAACgnnFpqImMjJQkHT161Gn70aNHHW2RkZE6duyYU3tFRYVOnDjh6POffH19FRwc7LQAAABczKWhJjY2VpGRkVqzZo1jm91uV1ZWlhISEiRJCQkJKioqUnZ2tqPP2rVrVVlZqfj4eFeWAwAAGpFaP/1UUlKi/Px8x3pBQYFycnIUFhamVq1aaezYsfrDH/6g9u3bKzY2VpMnT1Z0dLQGDhwoSercubP69++vESNGaN68eSovL9eYMWM0ePBgnnwCAABXrdahZsuWLbrjjjsc6+PHj5ckDR06VAsWLNCzzz6r0tJSjRw5UkVFRbr11lu1cuVK+fn5OV6zcOFCjRkzRomJifLw8NCgQYM0a9YsFxwOAABorGzGGFPXRdSW3W5XSEiIiouLXX9/Tfbb0sdPSffMknoOde3YAAA0Ym59/1YDefoJAADgSgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAEgg1AADAElweatq0aSObzVZlGT16tCSpX79+VdpGjRrl6jIAAEAj4+XqAb/++mudO3fOsb5z50797Gc/089//nPHthEjRujFF190rAcEBLi6DAAA0Mi4PNS0aNHCaX3atGm6/vrrdfvttzu2BQQEKDIy0tW7BgAAjZhb76k5e/as/vu//1vDhg2TzWZzbF+4cKGaN2+uLl26aNKkSTp16tRlxykrK5PdbndaAAAALubyMzUXW758uYqKivToo486tv3iF79Q69atFR0dre3bt2vixInKy8vTBx98cMlxMjIylJ6e7s5SAQBAA2czxhh3DZ6cnCwfHx99/PHHl+yzdu1aJSYmKj8/X9dff321fcrKylRWVuZYt9vtiomJUXFxsYKDg11bdPbb0sdPSffMknoOde3YAAA0Yna7XSEhIe55/5Ybz9Ts27dPq1evvuwZGEmKj4+XpMuGGl9fX/n6+rq8RgAAYB1uu6dm/vz5Cg8P11133XXZfjk5OZKkqKgod5UCAAAaAbecqamsrNT8+fM1dOhQeXn9/y727t2rRYsWacCAAWrWrJm2b9+ucePGqW/fvurWrZs7SgEAAI2EW0LN6tWrtX//fg0bNsxpu4+Pj1avXq2ZM2eqtLRUMTExGjRokF544QV3lAEAABoRt4SaO++8U9XdfxwTE6MNGza4Y5cAAKCR47ufAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJRBqAACAJbg81EydOlU2m81p6dSpk6P9zJkzGj16tJo1a6bAwEANGjRIR48edXUZAACgkXHLmZobb7xRR44ccSxffPGFo23cuHH6+OOPtXTpUm3YsEGHDx/WAw884I4yAABAI+LllkG9vBQZGVlle3Fxsf72t79p0aJF+ulPfypJmj9/vjp37qzNmzfr5ptvdkc5AACgEXDLmZo9e/YoOjpabdu2VWpqqvbv3y9Jys7OVnl5uZKSkhx9O3XqpFatWikzM/OS45WVlclutzstAAAAF3N5qImPj9eCBQu0cuVKzZ07VwUFBbrtttt08uRJFRYWysfHR6GhoU6viYiIUGFh4SXHzMjIUEhIiGOJiYlxddkAAKCBc/nlp5SUFMfP3bp1U3x8vFq3bq2///3v8vf3v6oxJ02apPHjxzvW7XY7wQYAADhx+yPdoaGh6tChg/Lz8xUZGamzZ8+qqKjIqc/Ro0ervQfnAl9fXwUHBzstAAAAF3N7qCkpKdHevXsVFRWlnj17ytvbW2vWrHG05+Xlaf/+/UpISHB3KQAAwMJcfvnpt7/9re655x61bt1ahw8fVlpamjw9PTVkyBCFhIRo+PDhGj9+vMLCwhQcHKwnn3xSCQkJPPkEAAB+FJeHmoMHD2rIkCE6fvy4WrRooVtvvVWbN29WixYtJElvvPGGPDw8NGjQIJWVlSk5OVl//OMfXV0GAABoZFweapYsWXLZdj8/P82ZM0dz5sxx9a4BAEAjxnc/AQAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAASyDUAAAAS3B5qMnIyFDv3r0VFBSk8PBwDRw4UHl5eU59+vXrJ5vN5rSMGjXK1aUAAIBGxOWhZsOGDRo9erQ2b96sVatWqby8XHfeeadKS0ud+o0YMUJHjhxxLK+++qqrSwEAAI2Il6sHXLlypdP6ggULFB4eruzsbPXt29exPSAgQJGRka7ePQAAaKTcfk9NcXGxJCksLMxp+8KFC9W8eXN16dJFkyZN0qlTpy45RllZmex2u9MCAABwMZefqblYZWWlxo4dq1tuuUVdunRxbP/FL36h1q1bKzo6Wtu3b9fEiROVl5enDz74oNpxMjIylJ6e7s5SAQBAA+fWUDN69Gjt3LlTX3zxhdP2kSNHOn7u2rWroqKilJiYqL179+r666+vMs6kSZM0fvx4x7rdbldMTIz7CgcAAA2O20LNmDFj9Mknn2jjxo267rrrLts3Pj5ekpSfn19tqPH19ZWvr69b6gQAANbg8lBjjNGTTz6pZcuWaf369YqNjb3ia3JyciRJUVFRri4HAAA0Ei4PNaNHj9aiRYv04YcfKigoSIWFhZKkkJAQ+fv7a+/evVq0aJEGDBigZs2aafv27Ro3bpz69u2rbt26ubocAADQSLg81MydO1fS+Q/Yu9j8+fP16KOPysfHR6tXr9bMmTNVWlqqmJgYDRo0SC+88IKrSwEAAI2IWy4/XU5MTIw2bNjg6t0CAIBGju9+AgAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAlkCoAQAAluBV1wXUV4eKTuuHQ8V1XUaNNW3io5ah/nVdBgAAdYZQ8x9+OF2uppJmrc3Xe6u+qOtyaszf21Orn7mdYAMAaLQINf/hVFmFmkoa3DtGj/S+ta7LqZH8YyUa+16Ofig9S6gBgHrmUNFp/VB6tq7LqLWGeAWAUHMJrcr2qNlfWkkjN0jRN9V1OQCABuhQ0Wklvb5Bp8vP1XUptdYQrwAQai7B//jO8z8c2UaoAQBclR9Kz+p0+TnNfPgmtQsPrOtyaqyhXgEg1AAA4GbtwgPVpWVIXZdheYQawOIa4vX8hngtH0DdI9QAFtZQr+c3xGv5AOoeoQawsIZ4Pb+hXssHUPcINUAjwPV8AI0BoQZAvZR/rKSuS6iVhngfEPdbwWrqNNTMmTNH06dPV2FhoeLi4jR79mz16dOnLksCUMeaNvGRv7enxr6XU9el1EpDuw+I+61gRXUWat577z2NHz9e8+bNU3x8vGbOnKnk5GTl5eUpPDy8rsoCLquh/Z9tQzvbIUktQ/21+pnbG9w8j30vR18XnNAPDejepYZ6v1VDm2dcO3UWambMmKERI0bo17/+tSRp3rx5WrFihd566y0999xzdVVWVUe2SVND+GRhNOj/s23axKeuy6iVlqH+Der/xBvy2aXesWENZq4b8jw3tL/BhqpOQs3Zs2eVnZ2tSZMmObZ5eHgoKSlJmZmZVfqXlZWprKzMsV5cfP7bs+12u8trO1l6WvYyo/Lv96uizEg5H0plRtqzWQps6/L9uULJSbsqy05p+7dHVHLS9XOC8779vlSlJSc17YGuatuiSV2XU2OhAT4K8iiX3V5e16VYVpCHtGxEdxWdajhnl6SG97vBPF87F95XSk7aZbfbXDbuhfdtY4zLxnRi6sChQ4eMJPPll186bZ8wYYLp06dPlf5paWlGEgsLCwsLC4sFlgMHDrglXzSIp58mTZqk8ePHO9YrKyt14sQJNWvWTDab6xKkdD5FxsTE6MCBAwoODnbp2KiK+b62mO9ri/m+tpjva6+2c26M0cmTJxUdHe2Weuok1DRv3lyenp46evSo0/ajR48qMjKySn9fX1/5+vo6bQsNDXVniQoODuaP4hpivq8t5vvaYr6vLeb72qvNnIeEhLitDg+3jXwZPj4+6tmzp9asWePYVllZqTVr1ighIaEuSgIAAA1cnV1+Gj9+vIYOHapevXqpT58+mjlzpkpLSx1PQwEAANRGnYWahx9+WN9//72mTJmiwsJC3XTTTVq5cqUiIiLqqiRJ5y91paWlVbncBfdgvq8t5vvaYr6vLeb72qtvc24zxl3PVQEAAFw7dXJPDQAAgKsRagAAgCUQagAAgCUQagAAgCUQai4yZ84ctWnTRn5+foqPj9dXX31V1yXVuY0bN+qee+5RdHS0bDabli9f7tRujNGUKVMUFRUlf39/JSUlac+ePU59Tpw4odTUVAUHBys0NFTDhw9XSYnzN9du375dt912m/z8/BQTE6NXX321Si1Lly5Vp06d5Ofnp65du+rTTz+tdS31XUZGhnr37q2goCCFh4dr4MCBysvLc+pz5swZjR49Ws2aNVNgYKAGDRpU5YMs9+/fr7vuuksBAQEKDw/XhAkTVFFR4dRn/fr16tGjh3x9fdWuXTstWLCgSj1X+puoSS312dy5c9WtWzfHB4clJCTos88+c7Qz1+41bdo02Ww2jR071rGNOXedqVOnymazOS2dOnVytFtyrt3y5QsN0JIlS4yPj4956623zK5du8yIESNMaGioOXr0aF2XVqc+/fRT8/zzz5sPPvjASDLLli1zap82bZoJCQkxy5cvN9u2bTP33nuviY2NNadPn3b06d+/v4mLizObN282n3/+uWnXrp0ZMmSIo724uNhERESY1NRUs3PnTrN48WLj7+9v/vSnPzn6bNq0yXh6eppXX33V7N6927zwwgvG29vb7Nixo1a11HfJyclm/vz5ZufOnSYnJ8cMGDDAtGrVypSUlDj6jBo1ysTExJg1a9aYLVu2mJtvvtn85Cc/cbRXVFSYLl26mKSkJLN161bz6aefmubNm5tJkyY5+nz77bcmICDAjB8/3uzevdvMnj3beHp6mpUrVzr61ORv4kq11HcfffSRWbFihfnXv/5l8vLyzO9+9zvj7e1tdu7caYxhrt3pq6++Mm3atDHdunUzTz/9tGM7c+46aWlp5sYbbzRHjhxxLN9//72j3YpzTaj5P3369DGjR492rJ87d85ER0ebjIyMOqyqfvnPUFNZWWkiIyPN9OnTHduKioqMr6+vWbx4sTHGmN27dxtJ5uuvv3b0+eyzz4zNZjOHDh0yxhjzxz/+0TRt2tSUlZU5+kycONF07NjRsf7QQw+Zu+66y6me+Ph489hjj9W4lobo2LFjRpLZsGGDMeb8MXl7e5ulS5c6+uTm5hpJJjMz0xhzPoh6eHiYwsJCR5+5c+ea4OBgxxw/++yz5sYbb3Ta18MPP2ySk5Md61f6m6hJLQ1R06ZNzV//+lfm2o1Onjxp2rdvb1atWmVuv/12R6hhzl0rLS3NxMXFVdtm1bnm8pOks2fPKjs7W0lJSY5tHh4eSkpKUmZmZh1WVr8VFBSosLDQad5CQkIUHx/vmLfMzEyFhoaqV69ejj5JSUny8PBQVlaWo0/fvn3l4+Pj6JOcnKy8vDz98MMPjj4X7+dCnwv7qUktDVFxcbEkKSwsTJKUnZ2t8vJyp+Ps1KmTWrVq5TTnXbt2dfogy+TkZNntdu3atcvR53LzWZO/iZrU0pCcO3dOS5YsUWlpqRISEphrNxo9erTuuuuuKvPCnLvenj17FB0drbZt2yo1NVX79++XZN25JtRI+ve//61z585V+TTjiIgIFRYW1lFV9d+FubncvBUWFio8PNyp3cvLS2FhYU59qhvj4n1cqs/F7VeqpaGprKzU2LFjdcstt6hLly6Szh+nj49PlS90/c+5uNr5tNvtOn36dI3+JmpSS0OwY8cOBQYGytfXV6NGjdKyZct0ww03MNdusmTJEn3zzTfKyMio0sacu1Z8fLwWLFiglStXau7cuSooKNBtt92mkydPWnau6+xrEgBc3ujRo7Vz50598cUXdV2KpXXs2FE5OTkqLi7W+++/r6FDh2rDhg11XZYlHThwQE8//bRWrVolPz+/ui7H8lJSUhw/d+vWTfHx8WrdurX+/ve/y9/fvw4rcx/O1Ehq3ry5PD09q9xpffToUUVGRtZRVfXfhbm53LxFRkbq2LFjTu0VFRU6ceKEU5/qxrh4H5fqc3H7lWppSMaMGaNPPvlE69at03XXXefYHhkZqbNnz6qoqMip/3/OxdXOZ3BwsPz9/Wv0N1GTWhoCHx8ftWvXTj179lRGRobi4uL05ptvMtdukJ2drWPHjqlHjx7y8vKSl5eXNmzYoFmzZsnLy0sRERHMuRuFhoaqQ4cOys/Pt+zvN6FG5/+j1rNnT61Zs8axrbKyUmvWrFFCQkIdVla/xcbGKjIy0mne7Ha7srKyHPOWkJCgoqIiZWdnO/qsXbtWlZWVio+Pd/TZuHGjysvLHX1WrVqljh07qmnTpo4+F+/nQp8L+6lJLQ2BMUZjxozRsmXLtHbtWsXGxjq19+zZU97e3k7HmZeXp/379zvN+Y4dO5zC5KpVqxQcHKwbbrjB0edy81mTv4ma1NIQVVZWqqysjLl2g8TERO3YsUM5OTmOpVevXkpNTXX8zJy7T0lJifbu3auoqCjr/n7X6rZiC1uyZInx9fU1CxYsMLt37zYjR440oaGhTnd9N0YnT540W7duNVu3bjWSzIwZM8zWrVvNvn37jDHnH6MODQ01H374odm+fbu57777qn2ku3v37iYrK8t88cUXpn379k6PdBcVFZmIiAjzyCOPmJ07d5olS5aYgICAKo90e3l5mddee83k5uaatLS0ah/pvlIt9d3jjz9uQkJCzPr1650ewzx16pSjz6hRo0yrVq3M2rVrzZYtW0xCQoJJSEhwtF94DPPOO+80OTk5ZuXKlaZFixbVPoY5YcIEk5uba+bMmVPtY5hX+pu4Ui313XPPPWc2bNhgCgoKzPbt281zzz1nbDab+ec//2mMYa6vhYuffjKGOXelZ555xqxfv94UFBSYTZs2maSkJNO8eXNz7NgxY4w155pQc5HZs2ebVq1aGR8fH9OnTx+zefPmui6pzq1bt85IqrIMHTrUGHP+UerJkyebiIgI4+vraxITE01eXp7TGMePHzdDhgwxgYGBJjg42Pz61782J0+edOqzbds2c+uttxpfX1/TsmVLM23atCq1/P3vfzcdOnQwPj4+5sYbbzQrVqxwaq9JLfVddXMtycyfP9/R5/Tp0+aJJ54wTZs2NQEBAeb+++83R44ccRrnu+++MykpKcbf3980b97cPPPMM6a8vNypz7p168xNN91kfHx8TNu2bZ32ccGV/iZqUkt9NmzYMNO6dWvj4+NjWrRoYRITEx2Bxhjm+lr4z1DDnLvOww8/bKKiooyPj49p2bKlefjhh01+fr6j3YpzbTPGmNqd2wEAAKh/uKcGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYAqEGAABYwv8CiVXxOKefsfEAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#THIS is the FINDSTILLBROKEN code\n",
    "print(\"quick classification: who has contiguity problems?\")\n",
    "nUnbroken, nNoEnclave, smallPieceLists, enclaveLists, sPgenerator, eLgenerator = 0., 0., list(), list(), list(), list()\n",
    "smallPieceLengths, enclaveLengths = list(), list()\n",
    "doubleTroubleList = list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%1000 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken:\n",
    "        nUnbroken +=1\n",
    "    if noEnclave:\n",
    "        nNoEnclave +=1\n",
    "    if not unbroken:\n",
    "        smallPieceLists.append(smallPieceList)\n",
    "        smallPieceLengths.append(len(smallPieceList))\n",
    "        sPgenerator.append(t)\n",
    "    if not noEnclave and unbroken:   #district is contiguous but contains 1+ enclave\n",
    "        enclaveLists.append(enclaveList)\n",
    "        enclaveLengths.append(len(enclaveList))\n",
    "        eLgenerator.append(t)\n",
    "    if not noEnclave and not unbroken:  #extremely discontig (\"broken\") HDs can appear to have enclaves;\n",
    "        doubleTroubleList.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",nUnbroken,\"contiguous and\",nNoEnclave,\"complement-contiguous HDs\")\n",
    "print(len(doubleTroubleList),\"HDs had both discontiguity problems, while enclave-only =\",len(eLgenerator),\n",
    "      \"and discontig only=\",len(sPgenerator)-len(doubleTroubleList) )\n",
    "\n",
    "print(\"here are the histograms of the small piece and enclave list lengths, total no =\",\n",
    "      len(smallPieceLists),len(enclaveLists) )\n",
    "plt.hist([s for s in smallPieceLengths],label=\"small piece l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.hist([e for e in enclaveLengths],label=\"enclave l units\",histtype='step',\n",
    "         cumulative=True,bins=[0,1,2,3,4,5,6,8,10,12,15,20,25,30,35,40,45,50,60,80,120,200])\n",
    "plt.legend()\n",
    "plt.show()\n",
    "print(\"And here are the small-HD-piece and small-enclave pops\")\n",
    "plt.hist([sum(unitPop[u] for u in s) for s in smallPieceLists],label=\"small piece 1 pop\",histtype='step')\n",
    "plt.hist([sum(unitPop[u] for u in e) for e in enclaveLists],label=\"enclave 1 pop\",histtype='step')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "id": "463db75a-694e-4c7d-9693-e10f3b4d65db",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Before addressing enclaves, let's triage the discontinuous HDs\n",
      "Now work on dropping smallish disconnected pieces that would keep us above 677646 district pop vs 713311 target\n",
      "we'll also trim any HD with total islands' pop <= 14266\n",
      "working on HD 763\n",
      "Out of 24 discontig HDs 24 had discontig HDs.\n",
      "Of these, 6 won't be under 677646 after all minor discontigys were shed, while 18 would be too underpopped if we trimmed the discontig pieces\n",
      "here is adjusted pop by original pop for those we trimmed and those we didn't (x)\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, reclassify after the trimming\n",
      "There are 18 HDs still with both discontinuity problems\n",
      "Additionally, 6 of the originally discontig HDs are now contig but still have an enclave\n"
     ]
    }
   ],
   "source": [
    "print(\"Before addressing enclaves, let's triage the discontinuous HDs\")\n",
    "#this is the CANTRIM code####\n",
    "\n",
    "#for t in sPgenerator:\n",
    "#    isContig, smallP = isContiguous(filledHDvtdList[t],unitNbrs)\n",
    "#    if isContig:\n",
    "#        print(\"oops!\",t)\n",
    "maxNudgeDownPop = int(0.02 * aDP)\n",
    "minPostFixPop = int(0.95 * aDP)\n",
    "print(\"Now work on dropping smallish disconnected pieces that would keep us above\",minPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "print(\"we'll also trim any HD with total islands' pop <=\",maxNudgeDownPop)\n",
    "nOrigIslands = [0 for t in range(nHDs)]\n",
    "totalIslandPop = [0. for t in range(nHDs)]\n",
    "tryToTrim, canTrim, cantTrim = list(), list(), list()\n",
    "for jj, t in enumerate(sPgenerator):\n",
    "    if jj%100 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    currList, shedList, shedPop = HDunitList[t].copy(), list(),  0.\n",
    "    done,newList = isContiguous(currList,unitNbrs)\n",
    "    if not done:\n",
    "        tryToTrim.append(t)\n",
    "        while not done:\n",
    "            shedList += newList\n",
    "            shedPop += np.sum( [unitPop[u] for u in newList] )\n",
    "            currList = list (  set(currList).difference(set(newList ))  )\n",
    "            done, newList = isContiguous(currList, unitNbrs)\n",
    "            nOrigIslands[t] +=1\n",
    "            \n",
    "        totalIslandPop[t] = shedPop            \n",
    "        if shedPop <= maxNudgeDownPop or HDvPop[t] - shedPop >= minPostFixPop:\n",
    "            canTrim.append(t)\n",
    "            HDvPop[t] -= shedPop\n",
    "            HDunitList[t] = list (set(HDunitList[t]).difference(set(shedList)) )\n",
    "        else:\n",
    "            cantTrim.append(t)\n",
    "print(\"Out of\",len(sPgenerator),\"discontig HDs\",len(tryToTrim),\"had discontig HDs.\")\n",
    "print(\"Of these,\",len(canTrim),\"won't be under\",minPostFixPop,\"after all minor discontigys were shed, while\",\n",
    "      len(cantTrim),\"would be too underpopped if we trimmed the discontig pieces\")\n",
    "plt.scatter([HDvPop[t] + totalIslandPop[t] for t in canTrim],[HDvPop[t] for t in canTrim])\n",
    "plt.scatter([HDvPop[t]                     for t in cantTrim],[HDvPop[t] for t in cantTrim],marker=\"x\")\n",
    "print(\"here is adjusted pop by original pop for those we trimmed and those we didn't (x)\")\n",
    "plt.plot([0.9*aDP, 1.1*aDP],[aDP, aDP], ls=\"--\")\n",
    "plt.show()\n",
    "\n",
    "print(\"Now, reclassify after the trimming\")\n",
    "badDiscoList, stillHasEnclave = list(), list()\n",
    "for t in sPgenerator:    \n",
    "    unbroken, noEnclave, __, ____ = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if not unbroken:\n",
    "        badDiscoList.append(t)  #will do a major triage on these later\n",
    "    if unbroken and not noEnclave:\n",
    "        stillHasEnclave.append(t)\n",
    "print(\"There are\",len(badDiscoList),\"HDs still with both discontinuity problems\")\n",
    "print(\"Additionally,\",len(stillHasEnclave),\"of the originally discontig HDs are now contig but still have an enclave\")\n",
    "eLgenerator += stillHasEnclave"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "id": "39d37c15-759f-462c-b503-047b6b5e1554",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 79 18\n",
      "{1025, 1798, 1799, 1800, 2312, 2313, 3854, 2322, 2330, 2332, 2333, 1315, 805, 2343, 812, 1836, 1589, 1081, 1849, 1094, 1096, 1098, 842, 1866, 3151, 1875, 601, 3932, 1380, 1126, 2409, 2410, 3693, 3694, 877, 1136, 2424, 2426, 894, 2433, 1155, 2436, 1159, 1705, 1706, 431, 433, 1724, 450, 451, 1986, 453, 965, 1759, 3044, 230, 1774, 1007, 3058, 757, 1782, 763}\n"
     ]
    }
   ],
   "source": [
    "print(len(discontigOnly),len(bothProblems), len(badDiscoList))\n",
    "print((set(discontigOnly).union(set(bothProblems)) ) .difference(set(badDiscoList)) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e16dfee-b5bc-4863-8bed-9a6b22290aaa",
   "metadata": {},
   "outputs": [],
   "source": [
    "#4/9 run below, pls -- but consider a shortcut to start from CCB + hdCPu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "id": "2e54bac4-c327-473d-bbb4-257486bddd20",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\n",
      "Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\n",
      "This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is 18\n",
      "swell-generating HD 802 our 1 th HD we must regrow out of 18 0 sec elapsed\n",
      "swell-generating HD 1775 our 11 th HD we must regrow out of 18 1001 sec elapsed\n"
     ]
    }
   ],
   "source": [
    "#THIS IS THE MUSTSPAWN code block\n",
    "print(\"And now, the major disco'd HDs (< 0.75 aDP in HDcP-contig portion and/or enclaves).  Redraw fully using HDswell\")\n",
    "print(\"Assuming we have run the previous canSwell block.  This block repeats the code, but starting from the home unit\")\n",
    "print(\"This takes 1 - 1000 sec per HD :-( The total number of HDs to fix is\",len(badDiscoList))\n",
    "avgDiam = MAP.area**0.5 / float(nDistricts)\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(badDiscoList):\n",
    "    if i%10 == 0:\n",
    "        print(\"swell-generating HD\",t,\"our\",i+1,\"th HD we must regrow out of\",len(badDiscoList),int(time.time()-startTime),\"sec elapsed\" )\n",
    "    notInCluster = True\n",
    "    for jj, geo in enumerate(CCBgeom):  #swell in-corner HDs from the corner cluster\n",
    "        if geo.contains(hdCP[t]):\n",
    "            starterU = allUnits.index(jj+0.25)\n",
    "            notInCluster = False\n",
    "    if notInCluster:\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]  #starter = unit with centroid closest to the hd center\n",
    "    contigUs = [starterU]  #we used getContigFromStarter(starterU, HDvtdList[t], unitNbrs) in above code block\n",
    "    contigPop = np.sum( [ unitPop[u] for u in contigUs ] )\n",
    "    gap = aDP - contigPop\n",
    "    origGap = gap\n",
    "    currList, addedList = contigUs.copy(), list()\n",
    "    adjoiners = getAdjoiners(currList, unitNbrs)\n",
    "    nearHDlist = [uu for uu in adjoiners]  #bias toward underused, close to HD (and its center)\n",
    "    nearHDscore = [ (0.2*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] for uu in adjoiners ]\n",
    "    stillGoing = True\n",
    "    \n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd:\n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else: #we selected the best unit to add legally\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((0.1*(unitUse[uu] - 1.) ) + 0.5*(unitCP[uu].distance(HDpoly[t]) + \n",
    "                                                                        unitCP[uu].distance(hdCP[t])  )  / HDdiam[t] )\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    for u in list( set(HDunitList[t]).difference(set(contigUs)) ):\n",
    "        unitUse[u] -= HDweight[t] * nDistricts       \n",
    "    HDunitList[t] = contigUs + addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72f83b6d-375b-45fd-924b-5b6be8aa6c63",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "id": "b78199da-ac7c-4cfb-ac0b-26363a8a8c56",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prev avg use and its sd are 1.01877 0.1316\n",
      "defining and displaying current unit use after most recent manipulations; compare to original farther above.\n",
      "current avg use and its sd are 1.01853 0.12939\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"prev avg use and its sd are\",r5(currAvg),r5(currSD) )\n",
    "print(\"defining and displaying current unit use after most recent manipulations; compare to original farther above.\")\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += nDistricts * HDweight[t]\n",
    "activeUnitDistro, activeUnitWeights = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > 0.1:\n",
    "        activeUnitDistro.append(unitUse[u])\n",
    "        activeUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(activeUnitDistro, weights=activeUnitWeights, bins = 20, histtype = \"step\")\n",
    "#plt.show()\n",
    "currAvg, currSD = getWeightedAvgAndSD(activeUnitDistro, activeUnitWeights)\n",
    "print(\"current avg use and its sd are\",r5(currAvg),r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "id": "a2242181-3a07-40b7-ae56-bbe47bd2dc79",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(not-so-)final check -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 501 time is now 16 sec\n",
      "working on HD 1001 time is now 42 sec\n",
      "working on HD 1501 time is now 64 sec\n",
      "working on HD 2003 time is now 85 sec\n",
      "working on HD 2503 time is now 102 sec\n",
      "working on HD 3003 time is now 108 sec\n",
      "working on HD 3503 time is now 114 sec\n",
      "working on HD 4004 time is now 133 sec\n",
      "out of 4106 total HDs, there were 3918 0 188 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 136 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"(not-so-)final check -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "id": "623fb818-67d9-458d-b854-4c70dfa449ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's fill in all enclaves that won't put us over 748977 district pop vs 713311 target\n",
      "working on enclave-y HD 54 . We have evaluated 0 of 4001 enclavy HDs.Time is now 0\n",
      "working on enclave-y HD 1614 . We have evaluated 100 of 4001 enclavy HDs.Time is now 15\n",
      "Out of 4001 HDs with enclaves 188 had enclaves.\n",
      "Of these, 188 wouldn't be over 748977 if all enclaves filled, while 0 were too populous\n",
      "here is enclave pop by final pop for those we filled\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#OPTIONAL if still enclaves -- rerun the CANFILL CODE  #check if sum of enclave pops small enough to add\n",
    "maxNudgeUpPop = int(0.02 * aDP)\n",
    "maxPostFixPop = int(1.05 * aDP)\n",
    "print(\"Now, let's fill in all enclaves that won't put us over\",maxPostFixPop,\"district pop vs\",int(aDP),\"target\")\n",
    "nOrigEnclaves = [0 for t in range(nHDs)]\n",
    "totalEnclavePop = [0. for t in range(nHDs)]\n",
    "tryToFill, canFill, cantFill = list(), list(), list()\n",
    "startTime = time.time()  #takes about xx sec per HD triage\n",
    "        \n",
    "for iii, t in enumerate(enclaveOnly):  #internals + edgers):\n",
    "    if iii%100 == 0:\n",
    "        print(\"working on enclave-y HD\",t,\". We have evaluated\",iii,\"of\",len(internals+edgers),\"enclavy HDs.Time is now\",int(time.time() - startTime) )\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and not noEnclave:  #\"and unbroken\" new 1/15 - discontig HDs will usually appear to have enclaves.  We'll fix these in later block\n",
    "        tryToFill.append(t)\n",
    "        enclaveLists = getEnclaveLists(HDunitList[t], unitNbrs)\n",
    "        nOrigEnclaves[t] = len(enclaveLists)\n",
    "        totalEnclavePop[t] = np.sum( [ [np.sum([unitPop[u] for u in eL])] for eL in enclaveLists ] ) \n",
    "        if HDvPop[t] + totalEnclavePop[t] <= maxPostFixPop or totalEnclavePop[t] < maxNudgeUpPop:\n",
    "            canFill.append(t)\n",
    "            for eL in enclaveLists:\n",
    "                HDunitList[t] += eL\n",
    "                HDvPop[t] += np.sum([unitPop[u] for u in eL])\n",
    "        else:\n",
    "            cantFill.append(t)\n",
    "print(\"Out of\",len(internals+edgers),\"HDs with enclaves\",len(tryToFill),\"had enclaves.\")\n",
    "print(\"Of these,\",len(canFill),\"wouldn't be over\",maxPostFixPop,\"if all enclaves filled, while\",len(cantFill),\"were too populous\")\n",
    "plt.scatter([HDvPop[t] for t in canFill],[totalEnclavePop[t] for t in canFill])\n",
    "print(\"here is enclave pop by final pop for those we filled\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "id": "18f46c40-7f28-4714-962f-0b462ff97b8a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "final ??? check -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 501 time is now 4 sec\n",
      "working on HD 1001 time is now 10 sec\n",
      "working on HD 1501 time is now 15 sec\n",
      "working on HD 2003 time is now 21 sec\n",
      "working on HD 2503 time is now 25 sec\n",
      "working on HD 3003 time is now 30 sec\n",
      "working on HD 3503 time is now 33 sec\n",
      "working on HD 4004 time is now 37 sec\n",
      "out of 4106 total HDs, there were 4106 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 37 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"final ??? check -- any more disco's ?\")  #run again if we ran above block to fill minor enclaves\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "id": "de4d8af8-cc64-4215-9b95-f4c6a2bd03af",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "savedAgainUnitList = [HDunitList[t].copy() for t in range(nHDs)] #safekeeping    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "id": "f4bb76c7-0ae0-40cb-9c6a-ee436dfc30c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDunitList = [savedAgainUnitList[t].copy() for t in range(nHDs)]  #restart"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "id": "f3bcd6a8-40b6-4764-a0d1-6814e3286cb8",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking on our corner clusters and unit county usage\n",
      "usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\n",
      "0.7793     0     5166 0.5\n",
      "0.95225     1     12598 0.5\n",
      "0.90016     2     11517 0.5\n",
      "0.88137     3     13921 0.5\n",
      "0.9578     4     6074 0.5\n",
      "0.77625     5     12062 0.5\n",
      "0.81154     6     6719 0.5\n",
      "1.05046     7     11308 0.5\n",
      "0.88791     8     9671 0.5\n",
      "0.95158     9     9838 0.5\n",
      "0.7462     10     3360 0.5\n",
      "1.2513     11     14065 0.5\n",
      "0.92704     12     11253 0.5\n",
      "0.74608     13     6506 0.5\n",
      "0.87853     14     9528 0.5\n",
      "0.95959     2725     314005 0.25\n",
      "0.97794     2726     148064 0.25\n",
      "0.96325     2727     216736 0.25\n",
      "1.00025     2728     65226 0.25\n"
     ]
    }
   ],
   "source": [
    "print(\"checking on our corner clusters and unit county usage\")\n",
    "print(\"usage, unit no, unit pop, type (0.5 = unit county, 0.25 = cluster) ...\")\n",
    "for u in range(nUnits):\n",
    "    if int(allUnits[u]) != allUnits[u] :\n",
    "        print(r5(unitUse[u]),\"   \",u,\"   \",int(unitPop[u]), allUnits[u]%1 )\n",
    "# note for MN, option 3 here led to tight CCB unit usage"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "id": "1e983c03-777a-4e81-bed0-34a620175f83",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "let's visualize over-used and underused units, < 0.75 or > 1.25\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here is the histogram of HD pops\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "minUnitUse, maxUnitUse = 0.75, 1.25\n",
    "print(\"let's visualize over-used and underused units, <\",minUnitUse,\"or >\",maxUnitUse)\n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minUnitUse:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(\"u\",unitCP[u])\n",
    "    if unitUse[u] > maxUnitUse:\n",
    "        plotPoly(unitGeom[u], 1.5)\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"and here is the histogram of HD pops\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist],bins = [0, 0.6*aDP, 0.7*aDP, 0.85*aDP, 0.9*aDP, 0.95*aDP,\n",
    "         0.98*aDP, aDP, 1.02*aDP, 1.05*aDP, 1.1*aDP, 1.15*aDP, 1.3*aDP, 1.5*aDP, 2.0*aDP])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "id": "9bc31b5a-992d-4a38-b9fe-3470b55e1e2e",
   "metadata": {},
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"option3redoContigButOffPopUnit.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "id": "7b9b68ef-6ae9-4d80-895d-41a86f48a55f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "hi\n"
     ]
    }
   ],
   "source": [
    "print(\"hi\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "id": "ee52659f-c922-41ea-90a2-04696a1b651f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2727]\n"
     ]
    }
   ],
   "source": [
    "needToBoostSet = {2727} #{2725, 2726, 2727}\n",
    "print(list(needToBoostSet))\n",
    "popRatios = [1.05] #[1.1, 1.1, 1.2] #recording the pop / aDP maximum for allowing tack-on of corner clusters for each of these underused corner clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "52701d21-2479-4989-a0c5-4b4e6ea0a6db",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "closeList = list()\n",
    "#plotPoly(unitGeom[CCBu])\n",
    "for t in range(nHDs):\n",
    "    if hdCP[t].distance(Point(-92.5,46.75)) < 0.2 and CCBu not in HDunitList[t]:\n",
    "        closeList.append(t)\n",
    "        plotPoly(vtdGeom[t])\n",
    "        plotCenter(t,hdCP[t])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "ed86f156-04eb-4991-913f-46e53ba6debb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "t = 1735\n",
    "for u in HDunitList[t]:\n",
    "    plotPoly(unitGeom[u], 0.3)\n",
    "    plotPoly(unitCP[u].buffer(0.003))\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plt.show()\n",
    "for v in HDtractList[t]:\n",
    "    plotPoly(vtdGeom[v], 0.3)\n",
    "\n",
    "plotPoly(hdCP[t].buffer(0.1))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "id": "12f08f77-664b-4ded-bfff-6409e19e4ca5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1721, 1722, 1725, 1726, 1730, 1731, 1732, 1733, 1735, 1736, 1737, 1739, 1740, 1741, 1742, 1743, 1744, 1745, 1746, 1797, 1842, 1880, 1882, 1884, 1887, 3913]\n"
     ]
    }
   ],
   "source": [
    "print(closeList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "id": "8273806c-0ea2-4c6b-b92b-6ca256235986",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "how much HD weight could pick up our CCB as a neighbor?\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the number (0-5) of added border units we can use to link the CCB to the current district 7\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on HD 1740\n",
      "we would boost unitUse of 2727 from 0.89519 to 0.90154 by attaching to all neighboring HDs with after-added pop no more than 1.15 aDP\n"
     ]
    }
   ],
   "source": [
    "print(\"how much HD weight could pick up our CCB as a neighbor?\")  #run this for each of of the underused corner clusters.  iterate on popRat\n",
    "boostWeight, CCBu = 0., list(needToBoostSet)[0]  #0 #1 #2 ...\n",
    "CCBnbrSet = set(unitNbrs[CCBu]) #set(get2nbrs([CCBu], unitNbrs))\n",
    "receivingList, linkerLists = list(), list()\n",
    "popRatio = 1.15\n",
    "maxBorderChainLength = int(input(\"enter the number (0-5) of added border units we can use to link the CCB to the current district\"))\n",
    "for jj,t in enumerate( [1740, 1745]): #(popHDlist):\n",
    "    if jj%800 == 0:\n",
    "        print(\"working on HD\",t)\n",
    "    if t in closeList: #HDvPop[t] < popRatio*aDP - unitPop[CCBu] :\n",
    "        if CCBu not in HDunitList[t]: \n",
    "            unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t]+[CCBu],unitNbrs)\n",
    "            if len(CCBnbrSet.intersection(set(HDunitList[t]))) > 0:  #the CCB adjoins the current district          \n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t]+[CCBu],unitNbrs)\n",
    "                if unbroken and noEnclave:\n",
    "                    boostWeight += HDweight[t] * nDistricts\n",
    "                    receivingList.append(t)\n",
    "                    linkerLists.append([])\n",
    "            else:  #no direct link.  Attempt an extended bridge   #NEED TO PROVE OUT THAT BELOW BLOCK WORKS **********\n",
    "                haveLinked, canBeLinked, chainLength, linkerSet, HDset = False, False, 1, set(list()), set(HDunitList[t])\n",
    "                HDborderSet = borderSet.intersection(HDset)\n",
    "                for u in HDborderSet:  #seed an initial linker set = border units adjoining the HD\n",
    "                    newLinkers = set( unitNbrs[u] ).intersection(borderSet.difference(HDset)) \n",
    "                    linkerSet = linkerSet.union(newLinkers) #these are border units directly adjoining the HD; to be expanded in loop below\n",
    "                while chainLength <= maxBorderChainLength and not haveLinked:\n",
    "                    CCBuLinkerSet = linkerSet.intersection(set(unitNbrs[CCBu]))\n",
    "                    if len(CCBuLinkerSet) > 0:  #there is a border bridge to link to the CCBu.  Below loop finds the minimal linker set\n",
    "                        usedLinkerSet = CCBuLinkerSet\n",
    "                        tryList = list(HDset.union(usedLinkerSet))\n",
    "                        canBeLinked = isContiguous(tryList,unitNbrs)[0]\n",
    "                        counter = 0\n",
    "                        while not canBeLinked and counter <= maxBorderChainLength:  #grow the minimal border link from the CCBu until it connects\n",
    "                            counter +=1\n",
    "                            usedLinkerSet = usedLinkerSet.union( set(getAdjoiners(usedLinkerSet,unitNbrs)).intersection(borderSet.difference(HDset)) )\n",
    "                            tryList = list(HDset.union(usedLinkerSet))\n",
    "                            canBeLinked = isContiguous(tryList,unitNbrs)[0]\n",
    "                        if canBeLinked:\n",
    "                            haveLinked = True\n",
    "                        else:\n",
    "                            raise Exception(\"Error! we thought there was a link for HD\",t,\"but after\",counter,\"loops we did not link up\")\n",
    "                    else:  #not yet linked; step further along the border\n",
    "                        newLinkers = set(getAdjoiners(linkerSet,unitNbrs)).intersection(borderSet.difference(HDset))\n",
    "                        linkerSet = linkerSet.union(newLinkers) #these are border units along a growing chain adjoining the HD                \n",
    "                        chainLength +=1\n",
    "                if haveLinked:\n",
    "                    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t]+[CCBu]+list(usedLinkerSet),unitNbrs)\n",
    "                    if unbroken and noEnclave:\n",
    "                        boostWeight += HDweight[t] * nDistricts\n",
    "                        receivingList.append(t)\n",
    "                        linkerLists.append(list(usedLinkerSet))        \n",
    "                   \n",
    "print(\"we would boost unitUse of\",CCBu,\"from\",r5(unitUse[CCBu]),\"to\",r5(unitUse[CCBu]+boostWeight),\"by attaching to all neighboring HDs\",\n",
    "     \"with after-added pop no more than\",popRatio,\"aDP\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 133,
   "id": "80a31b87-f520-47e9-b9d0-484676461581",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1740, 1745]\n"
     ]
    }
   ],
   "source": [
    "print(receivingList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "677035db-b16e-4e50-a9cd-4556f7ecaf59",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[34, 160, 162, 167, 436, 438, 853, 874, 2325]\n"
     ]
    }
   ],
   "source": [
    "print(receivingList)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "id": "c5e3eab6-7909-46c8-b15b-423d9cbad78a",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plotPoly(unitGeom[CCBu],0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "id": "bb8ffee8-4201-44e1-a61d-cf80f1f8a2e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "602331.3511953641 1.1482600015986897\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "599191.8380235536 1.1438586817384595\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "593312.4573311908 1.135616309883008\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "597891.429185126 1.1420356235336457\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "599636.114221895 1.1444815176840912\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "594457.2012668282 1.137221139658541\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "596626.9999999999 1.1402630056213148\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "595420.2683419425 1.1385712745401186\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "562570.6216327901 1.0925189745336314\n"
     ]
    },
    {
     "data": {
      "image/png": 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pBBkTEyhZOYG4RBt1la0RZZuqIztXj6RDVW5+vOk491xVRFbS0PUZGk6S+AghhBhxGlpMJT5dfvft9/lkiwIC/Onf9/Q63tbo4xff/GDIr3v6SBOnjzRdsIzNMbIf6U3tfh74n91MyUzgwTXTRvTal0ISHyGEECNPJ7aafDq1t5kUX55Dhd3k1x+d5tb5eVw/OyfUWbtrZukeMz63bz1EwvLZnduhY+3bDhG/cBq60x4xS3XkzNOds0n3nFW6R/3aObNQ251WkjPjRu598AW5+/mdNHcE+N3fX4HDahmxa18qSXyEEEKMOE2LzRYfpSCzIInVV0/EnWXn3946hjvTxiPXF/c5L07jYZ20ORkR+5qOQOqCnJEKecjVtnq5+xcfcaKujRfvuZzJGaN/CHtPkvgIIYQYcRrEzDw+5+pqaHlozXQSHFa+++phKuo7+Ne1c0k+Z1JGrY/5C+MWTKHplfe6+3Z31me0dJBx1/XDF/gQ2H2qia++uIeAYfKbrywb9ctT9EUSHyGEECNO02PyTlcvf3dVEflpLr7+24+54T+28L3PzGP51O4WHqOlg6bfvdeZ6XXu1M75l9Ax3eVgtPIHTX6yuYz/ePsYJROS+dG6hUxIGblba0NJEh8hhBBREGPDui7g+tk5zJmQzMO/2cu6/9rOzXNyefSmYiamusj48uhuwemPd0tr+Ze/HKK8vp0Hrp7KV1dPw2YZ2iHxI0kSHyGEECMu1oazd1Gq71mn81LiePHvLucPe8/w1GtHWP1/N/P5y/K5d+WUmGwZUUrxYVkDP3z3OB+WNbCsKJ0frVtIcU7sTwAsiY8QQogRp+kapqFoa/L23Nv9TOtzd4/jfS+5oPVxG0mL3Dj/OedsRBQNb5w/W9N1jdsXTuT62Tn87P2TPPfBSV7Yfopb5uZyx5JJLJmcNuRLRQy1Dn+Qv+6r5lfbKvj4dAslE5J49ouLuG5W9qiPvb9kyQohhBAjbtfr5Wz7w4lohzEoCxaaJGS29dHy07Uj9LHqD5rsO93C3spmmjoCpMXbmJWbxLTsBDISHPSZhV3UuR2FBl7W4vMy63OfC2/7gyYfltXz+oEa/rKvmjZfkCunZvB3V01m5fTMqCc8smSFEEKImDdn1UQy8xO720/OmbW4F9Xn04j7ZX2eGnFe35Wc95J9HNA0jWBcMzNmTutXQrCI0Hpd20828uudp/jPw7W01QUpTHdxdXEWSyens3RyGqnx9ovWNVSOHTtGWV0b2040sLWsgc2ldbT6guSnxfHl5YV8ZnE++Wmjf7HRwZIWHyGEEGIAjh07xrRpg5up2Bc0+PB4A28equH94/VUNnoAmJqVwOy8JGbnJVGck0Rhejy5Kc5L7kTc5gtS2djBibp2DlW3cKjKTU1lBYc7XFh0jZIJyVw9I5PrZ+dQnJMY9dadvkiLjxBCCBGjHFYLVxdncXVxFgCnmzrYdqKRjyubOVjVwsZDZ+nwh1Zkt+gaeSlOshKdpLrspMXbSI6z4bBasFl07FYdUyn8QZOAYeIJGDR3BGhs99PY7qeq2UNDuz987ewkB7Nyk1gxI4NH5s9mcWEaCSO8zMVoMP5esRBCCHEJhrJVZGKqi08vcvHpRRMBMEzF6aYOTjV2P+pb/TR1+Dl6tg23J4AvaOI3TPxBE4uuYbNo2K06TquF1Hg7aS47JROSuHZWNpPSXOSnuShMd5GeEJon6Pjx40ydmjVkryHWSOIjhBBCjBIWXaMgPZ6C9NhaBiKWxO4MREIIIYQQAySJjxBCCCHGDUl8hBBCCDFuSOIjhBBCiHFDEh8hhBBiAPx+/8ULiVFLEh8hhBBiAEbjJH8DMU7mLT4vSXyEEEKIAbDZbNEOQVwCSXyEEEKIcSTWW6wu1SUlPk899RSapvHQQw9F7N+6dSvXXHMN8fHxJCUlsWLFCjwez3nrefzxx9E0LeJRXFwcUcbr9XL//feTnp5OQkICa9eu5ezZs5cSvhBCCDEopmlGOwQxSINOfHbu3Mmzzz7L3LlzI/Zv3bqVG264geuuu44dO3awc+dOHnjgAXT9wpeaPXs21dXV4cf7778fcXz9+vX8+c9/5re//S2bN2+mqqqK22+/fbDhCyGEEINisVgwDCPaYYhBGtSSFW1tbaxbt46f/vSnfOc734k4tn79er72ta/xzW9+M7xvxowZFw/EaiUnJ6fPYy0tLfzsZz/jxRdf5JprrgHg5z//OTNnzmTbtm1cfvnlg3kZQgghoqilI8DB6hYANDQ0DTTobPnvet5VWuNCd2h6Hup5K2c4buo01rYTqDuGw2YLB6id8y/aOfu6dveMTdN77CeiLq3rgE73c63HexDxXA+f312NBmhoPdocuuIIeMf3qLRBJT73338/N998M2vWrIlIfGpra9m+fTvr1q3jiiuuoKysjOLiYr773e9y5ZVXXrDOY8eOkZeXh9PpZNmyZWzYsIFJkyYBsGvXLgKBAGvWrAmXLy4uZtKkSWzdurXPxMfn8+Hz+cLbbrd7MC9VCCHEMNlT2cQVUzJQKLoGGilF5DahUUiq81hfyU/EICXV8+nwjF5qPOIke1Y6ul0PXSMUdMRoKRW+E2b2eG3drwtl9niuIp93xW2CMlXn+6HCL1Qpwq9TdV2o830jXEx1x3NObGke55C8D7FqwInPSy+9xO7du9m5c2evYydOnABCfXa+973vMX/+fH75y1+yevVqDhw4wLRp0/qsc+nSpfziF79gxowZVFdX88QTT3DVVVdx4MABEhMTqampwW63k5KSEnFednY2NTU1fda5YcMGnnjiiYG+PCGEECPIbo29MTYuq4WknBQ0S2x2EvaWNkY7hKga0E9cZWUlDz74IC+88AJOZ++Msauz13333cddd93FggUL+P73v8+MGTN47rnnzlvvjTfeyGc+8xnmzp3L9ddfz6uvvkpzczO/+c1vBvhyuj366KO0tLSEH5WVlYOuSwghxNALGrE5n4ymiNmkB+i72WwcGVCLz65du6itrWXhwoXhfYZhsGXLFp555hlKS0sBmDVrVsR5M2fO5NSpU/2+TkpKCtOnT+f48eMA5OTk4Pf7aW5ujmj1OXv27Hn7BTkcDhwOR7+vKYQQYmR5AtJBWIy8AbX4rF69mv3797N3797wY/Hixaxbt469e/dSVFREXl5eOAHqcvToUQoKCvp9nba2NsrKysjNzQVg0aJF2Gw23n777XCZ0tJSTp06xbJlywbyEoQQQowSSXEyEaAYeQNq8UlMTKSkpCRiX3x8POnp6eH9X//61/n2t7/NvHnzmD9/Ps8//zxHjhzh5ZdfDp+zevVqbrvtNh544AEA/vEf/5FPfOITFBQUUFVVxbe//W0sFgt33HEHAMnJydx99908/PDDpKWlkZSUxFe/+lWWLVsmI7qEEEII0W+DGtV1IQ899BBer5f169fT2NjIvHnz2LhxI1OmTAmXKSsro76+Prx9+vRp7rjjDhoaGsjMzOTKK69k27ZtZGZmhst8//vfR9d11q5di8/n4/rrr+dHP/rRUIcvhBBihIz3NaNEdGhqnPzkud1ukpOTaWlpISkpKdrhCCHEuLeptJZVM7KiHcaA7XjnJEuumRztMAbNW9qIc0ZatMPot6H+/I69cYRCCCHGBIuuYZjj4ru3GEUk8RFCCBEVpgJ9fI+sjo5xPpxdEh8hhBBRoZQa9yuFi5EniY8QQoiokKRHRIMkPkIIIcRAxHq3pPExpum8JPERQgghBkIaqmKaJD5CCCGEGDck8RFCCCEGQPfG+Bpj47xv1ZDP3CyEEEL0R0q7yV/ePBHtMAYs0Wtw/M2K7r4yPROJc/vPXOxYFPrbxOfEkzviVx09JPERQggRFSl2K/OuK4p2GOPOqYMN0Q4hquRWlxBCiKgY3zdcRLRI4iOEEEKME0qpcZ9xSuIjhBBCjBfjewofQBIfIYQQYtxQgDbOm3wk8RFCCBEV0vgQBXKrSxIfIYQQ0THOP3+jQsG4f+Ml8RFCCCHGkXGe90jiI4QQIjo8bYFohzD+yP1FSXyEEEJEhzPBFu0Qxh/FuF+yQhIfIYQQYpxQKLnVFe0AhBBCCDFCQuPZxzVZq0sIIcTgBTxQc6Dz9sk5n6iaBom5kHT+JTGVUmjj/NbLSBvvb7ckPkIIIQbv5HuQPgVcaaHtnquNKwWnd5438dE1LTStzDj/IB5J0rdZEh8hhBCXwpkMCVngSOz7uOX8HzOaRUMZCnTJfEaMTOQjiY8QQowFrQ311J06ia6NTNfNrpYDu7sS68HtKN0ePqb16EKrofC0pfY6TwOayjsIlE3AYrOMSMxDxWhqxq9aoh3GoBiGSersyUBKtEOJGkl8hBBiDGiprSF/5hxsTucIX3nRoM+0Nu8la1EO9kTXEMYz/JpeOUXq7SuiHcagKNOk/cOtQEG0Q4kaGdUlhBBjQSyO1lGgtBjsdaJiMOZOmq6DMqMdRlRJ4iOEEGOAUmZs9hKOwZBj8n0WYZL4CCHEGBAaHRVjf9JlFmERBTH2WyKEEKJvKvZyCBX+jxhRsfaDMrQk8RFCiDHA09oae11PNE0mL4yKWPtBGVqS+AghxBgQn5KCMo1ohzEwKqb7Ccck0+NBcziiHUZUyXB2IYQYA5zxCVTs24vVZuvuN9Mjq0jOziE1d0KUohOjhenxoMfHRzuMqJLERwghxoCMSYVkTCo87/HyvbtGXeKj+U3G+22XkaaCQTTr+P7ol1tdQggxDozK9MIhH0EjzjBCc/mMY+M77RNCiDHCXVdLbfkJLDZbxP6ursO6PhqXhdAwzfE9md5IU8Eg2jk/I+PNJaV9Tz31FJqm8dBDD0Xs37p1K9dccw3x8fEkJSWxYsUKPB7PeevZsGEDl112GYmJiWRlZfGpT32K0tLSiDKrVq1C6xwB0PX4yle+cinhCyHEmNHR0syE4llMnr8o4lHY+SiYOz/aIfamMUqbosYuFQiAVRKfQdm5cyfPPvssc+fOjdi/detWbrjhBq677jp27NjBzp07eeCBB9Av0LS2efNm7r//frZt28bGjRsJBAJcd911tLe3R5S75557qK6uDj/+z//5P4MNXwghxhRN11GxNkRKB8wYiznGqUAQzTa+b/YM6tW3tbWxbt06fvrTn/Kd73wn4tj69ev52te+xje/+c3wvhkzZlywvtdffz1i+xe/+AVZWVns2rWLFSu6F4JzuVzk5OQMJmQhhBjbNA0VY7eNNF2D2Ao55qlgQG51Deak+++/n5tvvpk1a9ZE7K+trWX79u1kZWVxxRVXkJ2dzcqVK3n//fcHVH9LSwsAaWlpEftfeOEFMjIyKCkp4dFHH6Wjo+O8dfh8Ptxud8RDCCHGqpicCFDXUMEYzHxirWWtp0Bg3I/qGvCrf+mll9i9ezc7d+7sdezEiRMAPP7443zve99j/vz5/PKXv2T16tUcOHCAadOmXbR+0zR56KGHWL58OSUlJeH9d955JwUFBeTl5bFv3z4eeeQRSktLeeWVV/qsZ8OGDTzxxBMDfXlCCBGTDAWHjlcSl+gOTeOjhbrQhPIhrfO51r1Ygd4zUeo+DpHLZ2la19HI5Errcb4WLttzJmYtsp4eFWudgbnNIPaT1dgMo8fFtO7n54m1O4aeu3ucF36q9z5+Tn0R6WLP63Sdq5/zZsQ6iwVlxNhEl0NsQIlPZWUlDz74IBs3bsTpdPY63tU7/7777uOuu+4CYMGCBbz99ts899xzbNiw4aLXuP/++zlw4ECvVqJ77703/HzOnDnk5uayevVqysrKmDJlSq96Hn30UR5++OHwttvtJj8/v38vVAghYkyTPY1WAtiMIEqF+gyrzrWwQs+7WylUj0YW1dm7OKJ/kFLhf1R4V4/zez7vsa97t+rVKNJ1jupRv7u6lpnNHdjbPBHXRfU+79z95xTqfm4OoI6IIM9TX1d1PfZpTjuxSo+LQ3k8kJoa7VCiZkCJz65du6itrWXhwoXhfYZhsGXLFp555pnwSKxZs2ZFnDdz5kxOnTp10fofeOAB/vKXv7BlyxYmTpx4wbJLly4F4Pjx430mPg6HA8c4n5ZbCDF+NHYEKZlRQFZi7y+lo1VFvINA0CBp4ayLFxZDQne5MC8wyno8GFDis3r1avbv3x+x76677qK4uJhHHnmEoqIi8vLyeg1FP3r0KDfeeON561VK8dWvfpXf//73bNq0icmTJ180lr179wKQm5s7kJcghBBjUoLTisMyGufqOT8jEMTiiN3Wk1ikxcVhNjREO4yoGlDik5iYGNHvBiA+Pp709PTw/q9//et8+9vfZt68ecyfP5/nn3+eI0eO8PLLL4fPWb16NbfddhsPPPAAELq99eKLL/LHP/6RxMREampqAEhOTiYuLo6ysjJefPFFbrrpJtLT09m3bx/r169nxYoVvYbTCyHEeKRrYMRYp1sjEMAe74p2GOOKpmmx3Tl7CAx51+6HHnoIr9fL+vXraWxsZN68eWzcuDHidlRZWRn19fXh7R//+MdAaJLCnn7+85/zpS99CbvdzltvvcXTTz9Ne3s7+fn5rF27lscee2yowxdCiJikaxpmjH2gmYFgr5mmxfBSpgmjchbvkaOpmJvxanDcbjfJycm0tLSQlJQU7XCEEGJIHapyk5Foj6k+Poff3Ubq1Mnk5GdHO5RxI1hXR7C+HufMmdEOpd+G+vN7fK9UJoQQY4SuQ4zNX4gRCKCP81mER5q0+EjiI4QQY4KuaeGh6bHCDASxyq2ukWUYaJbx/dE/vl+9EEKIqDGDQWnxGWHS4iOJjxBCiCgxDRPLOG99GHGmKS0+0Q5ACCHE+GQCVn0MLAMRQ5RhhDqEjWPj+9ULIcQYEmtjdE1TyYfQSFPqnEXOxp/x/eqFEGKMiMV2ExOwSIvPCJP3WxIfIYQQUWFVJn75GBpZGpGr1I5D8hMnhBAiKpSpsFikBWJEmabc6op2AEIIIcanoKmwj/MRRiPNcLuxpCRHO4yokgkUhBBiDPBbNX5zsIpEx4X+rHf1fh4drSwZdUeY/8fjnVvDEdP5entf2rWCdXV4gxMvqY5oCVZXk/PE49EOI6ok8RFCiDFAd1j48uJ8ch32aIfSbx/r04lbeGu0wxgwzx/+g8xPfSXaYQxK23vvh1ZoH8ekjVEIIcYAE7CMkpacsS/G5g0QESTxEUKIMcBUinH+RV6IfpHERwghxgBDgSXGMh+bpyHaIQxSbL3PIpIkPkIIMQaYxN4syIG4tGiHIMahWPs9EUII0QczBlt8hIgGSXyEEGIMMFXstfjELuncHMvk90QIIcYAA9BjrsUn1uIVY4EkPkIIMQaYSiHrfY4UeaNjmSQ+QggxBphK5vERoj8k8RFCiDHABGnxEf0g/ZMk8RFCiDEgdKtLMp+REcvJg/yMSOIjhBBCDIDZ3hHtEMQlkMRHCCGEGADNbot2COISSOIjhBBjQGMgGO0QBixWbxhptlhOfGL1XR861mgHIIQQo423PUDdqda+D56ni0Sfu8/T56bvsuep97xdMs450N7OS02N2DVw6JHfaXt2etZ6VKhdbLvzuRY+rvWIR4uIL/JYZD2oyA/briONDY0UfPzWeV5fZ9nwa9HCZyqtc1vTeuzXuouFr9tzu0cMPeIJxanOOalnOa3X/uDZU7Rs+7DH+fT4H9XzTQBN07ve2M6HHirRua1ZLGiajqZ3bqOhaZ3vpaajoTq3O+tRCmWaqM5/UQrTVChlokwTr6eDQHs7aVY7ulK9foD0hATGO0l8hBDiHGfL3eQXp0Z+aKje35T7/O7c184+9qm+dw76GhM+LGfWgqkohwW/qVCd8YaLqsgrmue8HtNUfR5TEK4rHLmKfA1K9Xze+5WF0ofeGVx9sx3b9Jy+XmFnXWY49h47u6IKPcLboX80FKrrWhGJD+dunBNnRNYWEfm5ZSxXrQPTFppDoLNcd4hdsaiuNy903DQ7DwU7d3UlK91Ji6Jrf9d73uP/Y2d5TdNDyZau421vo67mTDgx0jQdp8uFPc7FxNXXYY2L6/N9He8k8RFCiD7olnN7Aozu0TDxiXEYfpPUlNj5Rl+fkEhCQUm0w4g5RjBI2a7tJOROY9qNt0S2romLksRHCCHGAIvVQtAwoh3GgPTRiCYuQinF0e0fMG3JFVhjuq9R9EjnZiGEOEcsfn/WNO2cW1IxINbiHQXOHDlIwZz5kvRcAmnxEUIIIUY5pRSVB/ejTBNXUnK0w4lpkvgIIcQYEJONJ9I3pd9aztYQl5hIZsHkaIcS8+RWlxBCnCMWcwiUkjxiDEvKzKKtsSHaYYwJkvgIIcRYEWOZT4yFe15GMECHuyU0ZH2Y1J0qJykze9jqH0/kVpcQQpxjjHwej3rKjJ22Nb/XQ135SfyeznW6emRtFqsVe5yL2hPHwx3MNU0ja/IUXMkpl3Td1sZ6ak+WkZCWQfrE/EuqS4RcUovPU089haZpPPTQQxH7t27dyjXXXEN8fDxJSUmsWLECj8dzwbp++MMfUlhYiNPpZOnSpezYsSPiuNfr5f777yc9PZ2EhATWrl3L2bNnLyV8IYQYO2Inh+g2ypt8goEA5fv2ULZrB7UnysiYVMDkBYtDj/mLwo9JJfPImTKNwvmLwscnzZmPu66Wk3t3cXLPR5zcu4vyvbs4deBj3PW1mP2ceqD25AmmLFpK9uQpw/xqx49Bt/js3LmTZ599lrlz50bs37p1KzfccAOPPvooP/jBD7BarXz88cfo+vlzrF//+tc8/PDD/OQnP2Hp0qU8/fTTXH/99ZSWlpKVlQXA+vXr+etf/8pvf/tbkpOTeeCBB7j99tv54IMPBvsShBBiTBndaURvoznv8ba1Uf7xLqZetgyr3T7g83WLhZyp03vtDwYCNNdUUVm9HzMYDE0+qGm9ZtbukpCaNojoxQWpQWhtbVXTpk1TGzduVCtXrlQPPvhg+NjSpUvVY489NqD6lixZou6///7wtmEYKi8vT23YsEEppVRzc7Oy2Wzqt7/9bbjM4cOHFaC2bt3ar2u0tLQoQLW0tAwoNiHE+FNxoD7aIQzYwV3HVH1NY7TDGJD3//qnaIfQJ9Mw1P53NyrDCEY7FKGG/vN7ULe67r//fm6++WbWrFkTsb+2tpbt27eTlZXFFVdcQXZ2NitXruT9998/b11+v59du3ZF1KXrOmvWrGHr1q0A7Nq1i0AgEFGmuLiYSZMmhcucy+fz4Xa7Ix5CCNEfnrZAtEMYF/wd7dEOoZfmszUc3f4h0y9fjq5boh2OGAYDTnxeeukldu/ezYYNG3odO3HiBACPP/4499xzD6+//joLFy5k9erVHDt2rM/66uvrMQyD7OzI3urZ2dnU1NQAUFNTg91uJyUl5bxlzrVhwwaSk5PDj/x86RQmhOifuITYmxW3paWV+CRXtMMYEEd8fLRDiFB9rBRvWyszll2J3SkLfI5VA0p8KisrefDBB3nhhRdwOp29jpudQ/nuu+8+7rrrLhYsWMD3v/99ZsyYwXPPPTc0EffTo48+SktLS/hRWVk5otcXQoiRpEyFM84R7TAGZDRNuuiur8NdX0vOlGnRDkUMswF1bt61axe1tbUsXLgwvM8wDLZs2cIzzzxDaWkpALNmzYo4b+bMmZw6darPOjMyMrBYLL1GaJ09e5acnBwAcnJy8Pv9NDc3R7T69CxzLofDgcMRW38EhBBisHx+X7RDiDltjQ3UVpxAQyM+NY3pl18Z7ZDECBhQ4rN69Wr2798fse+uu+6iuLiYRx55hKKiIvLy8sIJUJejR49y44039lmn3W5n0aJFvP3223zqU58CQi1Hb7/9Ng888AAAixYtwmaz8fbbb7N27VoASktLOXXqFMuWLRvISxBCjHIbKzbisrroGuOijfBYJQ2NJn87uz4M9qu8J3CABYkzB329cxs9tD729YcroYX9+ysGHUdvXVEM3/uvOZrY997zfR4zTC8dbccxMUiIn0FKyuJQE1E/hoKdW6Kv9xhAs1goWnDZgOMWsW1AiU9iYiIlJSUR++Lj40lPTw/v//rXv863v/1t5s2bx/z583n++ec5cuQIL7/8cvic1atXc9ttt4UTm4cffpi//du/ZfHixSxZsoSnn36a9vZ27rrrLgCSk5O5++67efjhh0lLSyMpKYmvfvWrLFu2jMsvv/yS3gAhxOgSZ41j+YTl0Q1iQv+L/nn/AWbOuWX4YhlHlFI0t3yEEWzFYnGRnPxldD32+luJ0W3IZ25+6KGH8Hq9rF+/nsbGRubNm8fGjRuZMqV78qWysjLq6+vD25/73Oeoq6vjn//5n6mpqWH+/Pm8/vrrER2ev//976PrOmvXrsXn83H99dfzox/9aKjDF0KIAbFYE6IdQswzDC8tLbsxjHaSkxdht8vcNWL4aEqNpu5lw8ftdpOcnExLSwtJSUnRDkcIcR7vn3mfKyfETl+LVw//mJtm/n20w4hZHR0VtLUdIT39KiyW2BqVJkbGUH9+y1pdQgghosbjKScj4xq5pSVGjKzOLoQYVUa6M/OlirV4Rxtdd2AYF17LUYihJC0+QohRpe8Vi0QsMgwfgUADSgXxeM9gmqEh91qP79wWiwubTbofiJEjiY8QQlwCv+Hh1cM/xml1saLoDqyWgS9oORYopWhvP4bXeyY85FzXHdht6WialeSkhVgsMreaiD5JfIQQo0YsjrX4ZMl6ANyeOt4o/SmaphMw/eiazrXTvoTTlhjlCIeOYXhoadkTarnRtIiWG1C4XFPIyLg6avEJ0R+S+AghRg1TmfiM2JyBOCkuk5tn3R/e9gTa+e2+f+PO+f8Li2X0dtzt6Cinw1OOhoam27FaEwkEmlEq2JnYhJJRpUx0i5Pk5IVYLL2XLBIiVkjiI4QYNTRNG9y0xaNQnC2elZNvZ0/VRhbn3xTtcM7L56slOWk+NlsKhuHDMFpJiJ+Oro/PW3Zi7JPERwgxauiajsM6dvqBTEwpYeeZt3BZ45iVG51bQKYZxO3eSzDYiqbpdC/YoOhaIMPnO4vNloLF4pB+OGLMk8RHCCGGia7rrJ3zMHvOvMnL+/6NyyeuZkLqglDL1jDqmeygaSQnLcBmSx7WawoRKyTxEUKIYbZgwnXMzV3NhxV/Yl/NVm7q0RdoKLW3n8DjKQdNJzlpoQwTF6IPkvgIIcQIsOgWAkE3VxV9bljqN4wOWty7ycv99LDUL8RYIYmPEGJE+U65UV7jvMc9TS1sOvNGxL6u/s7aBfb17BM9kH3n9qXua99QqWivZ9Oxb4WvYyqDmzIupzAuZ8B1GW4fRosPZ0k6lgQbFt1FRroMJRfiYiTxEUKMKOU1cE5PPe/xa7l5BKMZadcP+AyjPUCwrgPlM0IJWWdWZp3hxJoRN+z9hYQYayTxEUKIUUaZCn95C6bXQE+wYcuJR3fKn2shhoL8JgkhxCihlMJ/qhWzzY+jKAU9Tv5ECzHU5LdKCDEivMeaQIHpDUY7lFHJV+HGbA9gz0/EUiCjsYQYLpL4CCGGhVKKYJ2HYKMXAGuqA1t2fJSjGn1MbxDf8Was2S4ckvAIMewk8RFCDIhh9B6RpWkauh5asFIphf9kqH+KLSce54xU6YDbB6UUvrIWlGHinJ0u75EQI0QSHyFEv7S1tdHc3ExzczMulyviWEtLCwsWLMD0BvEebsQ5IxXdNXoX5ow2ZSo8B+pxTEnBEi/vkxAjSRIfIcRFNTc3U11dTUZGBiUlJeH9FRUVBAIBUlJSANBsltAENRZpvbgQz/46bNnxkvQIEQWS+AghLur06dPMnj271+2Y5uZmWltbycjIAECzaGh2C8htmwvSE+xYkmT1cyGiQRIfIcQFlZWVkZ+f32cflEAgwLRp00hODi2AqQImmk1Ht1v6XX9b7Qlazx4Gs2u+ZAVYSMgoJnFC0RC8gtFFBU2Uz5BbgUJEiSQ+QojzOn36NImJieHEpovP56Oqqgqfz0d2dnZ4v+dwA3Gz0vtdf92RLVhsLnJm3ohm1cP7TTNI7eE3aW8sJSFrBoH2VnxtNSRNLMGVNiGiDqUUHfWn6KivACvYEzKwO1Ox2hKwxLnQLf1PwoaTMhW+E80on4Fj6vlnrhZCDC9JfIQQEWpqamhtbQUgLi6OrKysXmVaW1vp6OggKSkJj+cU7e1lGO0BAu3tWA52tmR0tRD1XFRLqc5dKrw/s3hFr/p13UrO7JswfB5aa45hT0oiaVIxTSd203RqV2frkxZa78owcKXlk1wwDxUw8bvr8TSeJhhsI+BpRcNCzpzr0S0j++dOBUx85S0oQ4XfCnthErpD/uwKEU3yGyiEQCmFafpRyo/NZkPTNLxeL9OmTeuzfHy8jWBwD6AwzMtJT1+FlqFBwdDGZXHEkVIwN7ydMX3ZRc9xJEe2pvjaGjh7cCNgYpoGCelFJOeX9H3yEPBXtmK0B9CsGvaCpAHd9hNCDD9JfIQYZ5Qy8fvr8Psb8fvrME0/um7jzJn9+Pw1xLuuwWbLJzX1/Ldjjh9/nVmzPo3N5hzByAfHkZBO7twbAag9vAlfe/2wXct7rAlrpgt7fuKwXUMIcWkk8RFinPB4TtPWdgRNt+KwZ2O3pxMfPw1dD/0ZCATSqKs7SE3Nn8nPv4kJE669QG2KtrYWoJ7U1IkjEv9QMI0AyvRT/fFfUCg0NHSri+zZ1/S7jo760zSd/ggNK2iKuMQJeFrPgALVYRCXnEMalw/jqxBCXApNKaUuXiz2ud1ukpOTaWlpISlJpoUX44PHc4a2tsNomgWHI4fExJkXPWf79qdxubKx2eLJzp6Hy5WOw5EQUebDD5+ixf0qdvscVl/zw+EKf0R0NJ6h8cSHWGw9JmXUNFAmCkVL7R5SshaiUChl4kzIJm3KUjRNw9dSixHw40zLC89c7XbvQ9OsJCbOitIrEmJsGerPb0l8hBjDmpp3khA/A5tt4D/z9fXHaXFX0lB/kAUL/i58W2vrtu/jikunpGQdllEyYmq4KBVKdnR9YK+zra0Uw/CQnDx/eAITYhwZ6s9vudUlxBhm0R0oNbjV0DMyppKRMRWb1cWBA/9De/sZkpOnEgg0Y0sqGBdrS2mahqYNPLlLSJhBXd3GYYhICHGpJPERYgzTNCtK9V5UdCAmTVrKpElLhyiisc00g7S27sPvrycpaV60wxFC9EESHyHGNCXLRwwzpRTNzTswjA40zUJS0lySkxdGOywhxHlI4iPEGCdpz/DxeqtocX9MWuoV2GzJFz9BCBF1kvgIMYY1erN5Z9deMhL0ixcetJ5TM48f3oCi0WPhvmtujHYoQogBkMRHiDHMZzq4YcFycpPjoh3KmPP6gWrWLs2JdhhCiAEazq+BQogo8/gNnNaxPeQ8GgKGSZzdiq6Pr1YuIcaCS0p8nnrqKTRN46GHHgrvW7VqVecQ0O7HV77ylQvWc275rse//du/hcsUFhb2Ov7UU09dSvhCjHl+w8Rule83Q+3DsgYuK5QV1oWIRYO+1bVz506effZZ5s6d2+vYPffcw5NPPhnedrlcvcr0VF1dHbH92muvcffdd7N27dqI/U8++ST33HNPeDsxUdbDEeJCgobCapFWiaHiCxrsONlIcpwNl116CggRiwb1m9vW1sa6dev46U9/yne+851ex10uFzk5/b/3fW7ZP/7xj1x99dUUFRVF7E9MTBxQvUKMd4apsOrS4nOpalq87D/Tgt2qs7gglXiHJD1CxKpB/UW8//77ufnmm1mzZk2fx1944QUyMjIoKSnh0UcfpaOjo991nz17lr/+9a/cfffdvY499dRTpKens2DBAv7t3/6NYPD8M9L6fD7cbnfEQ4jxxlAK6YYyOC2eAJuP1vH24bPUt/lYMzOLldMzJekRIsYN+Df4pZdeYvfu3ezcubPP43feeScFBQXk5eWxb98+HnnkEUpLS3nllVf6Vf/zzz9PYmIit99+e8T+r33tayxcuJC0tDQ+/PBDHn30Uaqrq/n3f//3PuvZsGEDTzzxxMBenBBjjFJqXCwtMZSChsnmo3XEO6xcMSUdm0VazIQYSwa0SGllZSWLFy9m48aN4b49q1atYv78+Tz99NN9nvPOO++wevVqjh8/zpQpUy56jeLiYq699lp+8IMfXLDcc889x3333UdbWxsOh6PXcZ/Ph8/nC2+73W7y8/NlkVIxrmwqrWXVjKxohzGqKaU4WOWmvs2HUoAGSyenSR8eIUaJqC5SumvXLmpra1m4sHs6dsMw2LJlC8888ww+n6/Xas1Ll4bW+OlP4vPee+9RWlrKr3/964vGsnTpUoLBIOXl5cyYMaPXcYfD0WdCJMR4Iq09ffMGDPZWNuPxGygUJXnJzM5LkvdLiHFgQInP6tWr2b9/f8S+u+66i+LiYh555JFeSQ/A3r17AcjNzb1o/T/72c9YtGgR8+ZdfHG/vXv3ous6WVnybVaMLGUoVODSFv7slwF/Bvc+ob7ZQ2OTJ3S080Nd61G8a5+uQ1DTUJ13dXQNtM6SeleZ8Dk9jxE+Fp5qoqt6revf6CYT3oDB4Wo3LZ4AmqZhKoUGXFaYJv11hBiHBvRbn5iYSElJScS++Ph40tPTKSkpoaysjBdffJGbbrqJ9PR09u3bx/r161mxYkXEsPfi4mI2bNjAbbfdFt7ndrv57W9/y//9v/+313W3bt3K9u3bufrqq0lMTGTr1q2sX7+eL3zhC6SmylwaYmR5jzehO4f5A7P/d6Av6KrkeMqONYRXlVCA6txQZs9LKd5ubiMvPylUJnz50BPT7K7TDNelwv92le/579C8gsHZ29qOjoYCiuKd/MPsCaTG26MYkRBitBjSv952u5233nqLp59+mvb2dvLz81m7di2PPfZYRLnS0lJaWloi9r300ksopbjjjjt61etwOHjppZd4/PHH8fl8TJ48mfXr1/Pwww8PZfhC9IumaTgKYqOfWFbnoz9a9lVxw5y84QxnyDUGgux19x41ektcDkUuudUthOhtQJ2bY9lQd44S45f3aBPO6WOvpfH1fVXcMDd2Ep9NjW7idJ3FyfFYpG+OEGNWVDs3CyHAaA9EO4RR44/lH/S5X9csfKLg8mG9tjtosipLvsQIIQZGEh8hBsjikl+bI03l7K4/TlPA5P5Z1/U6/ofzJERDxVCKOJmZUQgxCDIzlxACAG0Ad73PtNdzuK29z6QHBjEgbYA2N7ZyRWrCMF9FCDEWyVdXIQQAqh/9ZOo9Tfy5cjd+02BhSlp4/67aw1R2NHYPZR+mGLtowGlvgBnxvafQEEKIC5HER4iBGqsdac9p8fndyfcxlIldt2CaJoYKorAwOyWX8tZ6PlV4Zbjs5MQc/lhdzuNzrkcf5kVRtze3ke2wMSPeOazXEUKMTZL4CDFQY2QgZMDTTv2xzaEJfTSd37vBW16ORmiCwlnJecxMK+rz3CXnjJHXNJ04LcBvTm7h81NWDVvMftOkzTBZmiK3uYQQgyOJjxDjVGvVYZInzsGVlg/AF6s/5oi7lgWpeczLmIWhgheto6a9ju8ceo+gCTdkZ1OQkDGsMR/v8DErQVp6hBCDJ4mPEOOUGQxgsXUnETWeVv5uxrXsOHuAN059yI6msyxNy2ZxxjSy4kNNPH4jwIc1+7FZHCzPmU1OfCb3TC5hZ305nypcPuwxn/b6mRkvQ9iFEIMniY8QAzVG+vhoDqg7uhmLLQ6Alo4kKIIl2aFlaW4qUASU4uelG8mJC91aavJ7WJ41nfK22vCQddM0+VzRFcMer1IKU0V/7S8hRGyTxEeIcSq9cBkUdm9P3FcVcVzTNOyaxn0zr+917rSUScMcXW9vNbi5LDl+xK8rhBhbZB4fIcSo91FLOzPinaTb5buaEOLSSOIjxECNkVFdsUIpRZ0/wKQ4WXRUCHHpJPERQoxqHza3cbkMXxdCDBFpNxZigJSpcL99avinJx4Cp6or0Sf0r1/MGavOC/vd/Sqb8OEHZOTnX0po/WLfsxvHui+Qmpo47NcSQowPkvgIMUCaVSfx6ny0GFgk0/Wum6JVJf0qO2sA9R49tI/pN/W9TtdQanXZiZN5e4QQQ0hudQkxUIqYSHqAmB9671q8GH95ebTDEEKMIZL4CDGWxXhHbM/ej3HOnRvtMIQQY4gkPkKMYbGd9oBjciG+Y8eiHYYQYgyRxEeIATLaA9EOod9i+0YX2CZMwGhoIHDmTLRDEUKMEZL4CDFAFlcMjQmI8T4+AAkrVuA5cDDaYQghxghJfIQQo1qgthY9QZaqEEIMDUl8hBCjmvfAARKWD//K70KI8UESHyHEgKkR7DatgsERu5YQYuyLoc4KQowOsT5SaijoNjulv/41KIWmaQTb2jCDQZJnziR/xYohvVbc3Lm0ffCBtPoIIYaEJD5CDFDsdxe+dNNuvy1i29fWxsf/9E/YEhIpfeklrC4XU269dUiuZc3OxldaOiR1CSGEJD5CDJSmoUwVO7M3jwBHQgJL/vM/w9tHf/2bIavbX16ObeLEIatPCDG+SR8fIQZKSdIzkuwFBfjKymh7/wOMtrZohyOEiHHS4iPEQI2BuXGG39D1hNJ0naTrrsP0+/EeOIDhdoNSWJJT0Bx2NIsFzWpFs9vRHI7QvxZL6BEXh6YPzfc7oz2A4fajvEGU34iM0WbBNjEB3W4ZkmsJIYaPJD5CiJig2+24Fi4EQCmF2d6O8vlQhgHBIMrvx2hpQfn8YBoow8Ds8IAyz6lJw5KSjDUtDUtaGprNhlIaKFA+A7M9gNHmByMyedNdNizJdrR0J5pNR+uRAJt+A39lKypgoll1HEXJ0iooxCgliY8YfUpfB4s11GjQcAwmLYO8+YOurqa9htdOvsakxEk4rc5LDk+dDDCpYnI/C3f+O5DPwMGcc57zGk41cFrfcvFTlUIzFHmko/enhaRr8dPztH6pA+U0mq9F7uzH61GGSconr8GSEHfBcpqmYUlIgISEi1d67jVME9PtJtjYSODAAVQgQPtH5STfcjOaw4Il0YY1Iw7N2v+WIt1uwTklBQDTF8Rb2giahh5nxZYbLy1BQowikviI0aepHGZ9EpJyoenkgJOeFl8LR5uO0uZvI94WT0ewgyR7Egn2BJbmLr3k8F49voVJKwsuuZ6RcPrtBlasWNivsmUfHSF36kRcKQNPJnpZNXtQp7XvOoT/5Bni5ky99BjOQ9N1LCkpWFJSoKgIAF9FC46i5CGpX3dYiZuZDoDpCRI43YoZMDuvreEoTEKzSSIkRLRI4iOibmPFRuKs3d/w2+xw/WvfQFv0t5A5o89z6jrq2FGzg2ZfM/My5zExYSInWk7QEexAKUVJRgk23YbNYsNhcQxpvFpMDWjXME2zX604ylToluiOd9B0C8o899bUSBie2Zn0OCuOopTuqwRMfBVuVNBE0zXsBYnoDvkzLMRIkt84EXUuq4vlE0KT03UEOvgg6OHgpCt57sBzzMucx+eCS9hfv5+3Kt5iSsoUluUt44d7f8hNk2/iirwrMJXJzrM7cVldXDnhyii/mtHFarEQDAax2+0XLWsaBrolui0RmtWC6Q9E48ojcxWbjnNqCgAqaOI/1YrpN0AD59RUNEssJdVCxCYZzi5GFa/hRUen2dfMNy77Bk6Lkx01O0hxpPCNy75BTXsNp9ynmJoylUR7IqnOVNLj0rm24Npw8iS6BY0gVkv/vt+YhoklyokPVh2CxsXLDbUo5BtdnaDjitNwFCbhPdIw8kEIMQ5Ji48YVdKcaawuWB3e/lzx5yKOf23h1wAkyeknBf2+fWUqM+ojkTSLFdOIQuIT5XVIfMeacRanRTcIIcYJafERQgBgBs0BjWQaDprNMm5afHqFEOX3Xojx4pJ+05566ik0TeOhhx4K71u1ahWapkU8vvKVr1ywni996Uu9zrnhhhsiyjQ2NrJu3TqSkpJISUnh7rvvpk1mcRXiggb6ea5Fe3JGqwWi0eITbTZJeoQYKYO+1bVz506effZZ5s6d2+vYPffcw5NPPhnedrlcF63vhhtu4Oc//3l42+GIHImzbt06qqur2bhxI4FAgLvuuot7772XF198cbAvQYhBUdr4Xp9dKYXh8dPe0ISmNHSrBd1iRbdYsLocWF0X70h9PrrFghmNFh8V3f+nymfI+m9CjJBBJT5tbW2sW7eOn/70p3znO9/pddzlcpGTkzOgOh0Ox3nPOXz4MK+//jo7d+5k8eLFAPzgBz/gpptu4nvf+x55eXkDfxFiVHvpxFYafG1oQHlbNV+YejVzU/MB+N8f/54UewLuQDtxVic2zcI/zLx2xGKLpeHshhHsVzmPu53Wo1WUe0Plu15hX3MpKgC7TlxKEqBQpolhBFGGQdATBL8ROuNCb5NSEZMfap31BpuacLmCDM2MOrHDOS01NOkhYE2Pw5Z18S+LQojBGVTic//993PzzTezZs2aPhOfF154gV/96lfk5OTwiU98gm9961sXbfXZtGkTWVlZpKamcs011/Cd73yH9PTQJGBbt24lJSUlnPQArFmzBl3X2b59O7fddttgXoYYJfa6W/jYvTFiX6O/lcfm3Q7AP25/joNNp3m3+iCmGaSyvZZ/mtf9/7y0pYYfHn6Tk63VfG/J345o7KOd6mdLRl19DVnLJ1FY0rsFdyT5GhuofvedKFw5usmsHtc96WGg3oPncANoGs5pMsRdiKE24MTnpZdeYvfu3ezcubPP43feeScFBQXk5eWxb98+HnnkEUpLS3nllVfOW+cNN9zA7bffzuTJkykrK+Of/umfuPHGG9m6dSsWi4WamhqysrIiA7daSUtLo6amps86fT4fPp8vvO12uwf6UsUwO9zm4bTXz9K8lSxOjj9vuScWrqMt6MVhsZNi772UwYzkHGYk5/DGmQN89+PfkxOXxt3TVw5n6DHDarX1q9zpsuMsWBb9kXKazY6Kxq2uUcSWEYctIw4VMPEeaUSPs2CfnBz9/ldCjBEDSnwqKyt58MEH2bhxI05n32se3XvvveHnc+bMITc3l9WrV1NWVsaUKVP6POfzn/98xDlz585lypQpbNq0idWrV/d5zsVs2LCBJ554YlDnipGR7bBR1uGjJWiwpbEVXQMdDYsGuqZhoXNNJg0smh2rqZHSo/tIR9DPlrOlaIDZeVNmYcYUtp49NKxxq2iPfR6A/kQaDPjx+XzEDWLdq6Fmsdswg9GYwHD00Ww6cbPTMTsCeA40YMt2yS0wIYbAgBKfXbt2UVtby8KF3Wv/GIbBli1beOaZZ/D5fL0mQFu6NLQ20vHjx8+b+JyrqKiIjIwMjh8/zurVq8nJyaG2tjaiTDAYpLGx8bz9gh599FEefvjh8Lbb7SY/P79f1xcjI81m5ZaslNBK24ChFIYKJTGmAlMpDAg/f6n8I94yWwFYmDEVHcV/H32VVGcKfzfjRux66Md5zozrhzXuWOrj0x8fvvEai1dcHe0wgFCLD8H+9UsaL3SXDdecDAI17XgONeCcmSatP0JcggElPqtXr2b//v0R++666y6Ki4t55JFH+pz1de/evQDk5ub2+zqnT5+moaEhfM6yZctobm5m165dLFq0CIB33nkH0zTDidW5HA5Hr5FhYnTSOlt3LH38Me8IdNDgbcBv+pkd18HqSdcBsH77z8h1ZfLZKdfitNh4p3o/Tb5W7LqVnLhU7pkxuJbC/gh2xE6LT38+HnWbncSkpGGPpT90XY+h9rSRZcuJx5LswPNxHc5Z6bLiuxCDNKDEJzExkZKSkoh98fHxpKenU1JSQllZGS+++CI33XQT6enp7Nu3j/Xr17NixYqIYe/FxcVs2LCB2267jba2Np544gnWrl1LTk4OZWVlfOMb32Dq1Klcf33om/vMmTO54YYbuOeee/jJT35CIBDggQce4POf/7yM6BpDWt9+G81mA4uFhOWh/iYvHnmR6wquC63nldfdB+X7S++mLeDli+/+C7+/7rvMTyug1uvmrNfNu1V7hzVOqyt2vm1rmoZpmFFffHT0i410S4+zEjc3E8/+OpzFabLAqRCDMKS/NXa7nbfeeounn36a9vZ28vPzWbt2LY899lhEudLSUlpaWgCwWCzs27eP559/nubmZvLy8rjuuuv4l3/5l4gWmxdeeIEHHniA1atXo+s6a9eu5T//8z+HMnwxzAzDoKOjo9f+1ud/iZ6aijU7G+uECQRPnMTi8RAXF4cFCw7lAANa2ltooSXi3JKUaTy1+ze4gx14gl5umnAZt+TM5WzL2WF7HW1uN01nG8OTbUJoZLam6923wXR6HA8N7Q5N0RJ6rmk6WlcuomnomtZZSaiVRtM0tM4V1S/ptoZ28ZFdFosFv8+HXVpIY4Kma8TNzcR7tAlMhS07Hmta330uhRC9aaq/411jnNvtJjk5mZaWFpJGSbP+eFNeXo7NZou4JaqUwqytRbW1gQrNCaNPmMCJqiqysrKoddfid/mjGHVvZ7cdZP70K1FmV0dnhTKhq9VAKQUq9K8i9Dw0QZ5CKTofnb92vcqce95gowyd+GHd++TOmIbT1ns0XJeAx4sz6A0nWtGmv/o+0+deft7j551bqMe+nm/b+fb13A60WtAnFww4VrP1DBO04zizozcNQLDJizXeh331nWDp3yg+IWLJUH9+SzupGBHBYBCfz0dBQUHvFow++n9N6OwIP4MZIxHegHxQ0cGsqxZevOAo4N8XoCBnKvlZRdEOpd/+qhRT1vxNtMPol47q43hOJ5J02SeiFoMdIOiDo2+AtbPlJyET0qaAI/oj9YQYbSTxEcPq+PHjeL1eDMMgMTEx2uEMCX9He7RD6Lfk+FRa2hpjKvEhhkYsaTYHyhgFw++tDph5S+i5UtBeBzX7wN91a7mzfSt1MmRMjUqIQowWkviIIWWaJsFgkGPHjmG320lMTGTq1LH1h9YRf/7JFkeblIQ0Ks+eiHYYAxJL8yTpFgcqOLpuxaJpkJAVevSkFDQch4O/h1mfiqkEU4ihJImPGBJut5va2lrq6+vJzc2loKCAhFEwId54l5yYwYGTu6MdxpilOxyoWJlwUdMgYxrEZ8KRv3a3EAkxzkjiI4ZEbW0tU6dOHXOtO7EuMS4Jjz92bs1BbE0QqVsdqKDv4gWjqakC6o919/Ku3gdZs8AISGdoMS5J4iMGRSnFyZMnaWtrQyk1ZvrvjDWapoWX84gVMXWry2pHGaN8pumGYzBtTff21DXnLyvEOCCJjxiwQ4cOYbPZSEtLo7CwMGI+GyHGk9EyBYAQov8k8REX1dzcTHNzM2fPniU9PZ3MzEwyMzOjHZYQ4nyO/DU00gugdfgm8xQiFkniIy6qoqKCWbNmkZ+fj8Vi4fDhw+GZtwFcLpcsHSIGxTRNqjwt6JhoKHJc6Wixc6dr9LI45JaWEOchiY/opaKiguPHj2O324HQUiR1dXURZXp2Yi4vL2f37t1kZUUOn+1rUvBz9ymlqGn109QRDPfsMMOzGneX6TqmepwX+vec7R7Hz728qRSa1uOcHmU1upeMgO5bd7oGFl3HomtYdA2rRaem/hR5h1+jc+0JNM2Cpul0LjYReijQ0EPX0jQ0pXVeT+u8sIamW7DHubA7XegWG7puQdMt6LoF3WLtXNbCiiV8bHC3VfRR2Fn4W3teIdmeRG3AZGFSMj4zyEvH/sIPr3w4hnr4dBllEfvawO6KdhRCjFqS+Ihe8vPzSU9Pj9jXsw/PuQlOYWEh+fn5+P295zPped6ZtjMcbjpMgi1ymPuOs0FME+ZPyGXxhK4+QxG1ROzrOqTrWtfRc7Z7nKl3JTBd615F1hGOT6nO5En1SKoUpqkImiaGYRIwTYKGSZ17IqlZM1GYoAyUqVCYKGXStc6EpnUla2bnlUJdjLWudSg0hWkaBLz1uJu9KDOIMg1M00ApA2WaoW1lolQQZZr0yuT6yaaODOq84XSkpQZLYiErM3K5ZUIWqCBnOmp5/fRePFYD92uvc+eNNwzb9X2eFioOv0tj9QniEtOYt+JLl1DbKEgsP34JXBmda3EoyF8S7YiEGLUk8RG96Lo+4Dl4LBYLcXHnXw8KQPNqLMxdSF5C5G2xVYWhf3/04bvcMGv2gK47dPr/4eVqz6PyaHn/qjtnEam2xnYy83OYMmfxQAMctPqjPz7vsY5gB89+/CzxtshJGU1loqNzpPEITy5/kgT70M7J9JuVf8/R1jreqznIr44foKqjgey4NBQKV24h1ir4w5b3sFp0blm+fEB17/vmN4grKiKusJBgaytBtxs0mLzui5z81X/jmphP5srlVB75iPbmJpbctIKTB96kofoYyRkTmLbgUwO6ntaPFp+A34fP24HN7sDhHMLWmLMHwV0NjsTIkVtCiPOSxEeMGE3TMJV58YKjnN2eTsmyywZ17u5336SoZHSs8/Xk1ifJisviqglXsTin70TsmT3P4LIO/W0TTdOYkZTFjKTu1kNvMMB3972MqRRLC5dy6MgxvB3tGIYRXth2/wfPoUwds70V51EPtqQMlGkSbG0laf4CclesJH7OHFQwyJnvfx+l6yQuX87Ue7/CrptuQpuUj/2227DZ41l03Zf58w/+kfJD71H20XZuuPdxju3+C9MWDOy1eDzttNeeCrf4eYzQ/dRQa11oVdqKna+SlD+L1poyltz6laF7I93VkD0b7LEzm7gQ0SaJjxgxVs1KTXsNZc1lWHQLbf42bLqN/RU6DqvGlIyMaIc4bEwzyIFtm5k4rTAqQ/+VUn1eV9f1C04YaNft6MM4ZPvdmiOUuWsAxdaavUxPmUx59QHKauK548ZPYDnn2skZU2h85mfYNbAtXE7GlVeRNGUquy5fSvt/v0Dtiiuxxsczdf3DBGprmfSFL9J28iSOjAyWbHyL6rc2UvvWRiw2G0ebtzPj8mvwe1spWjyfV3/0zyz55B0Dfg2H25Ow15ygq+3nV5uP4HI5WbNwOnFOGxoakxbfSG7BdHa8Ucu+Tb8jKbuAwplD0OpXsAwaT0LFBzDn05denxDjgCQ+YsTkJeThNbykOdOYnDw5/EFs9dWxcnoMDY8fRFcbv89DR4sPaxS+mdt0Oz7Dh7Nr5e5O/7zsnwH4we4f8G7lu8xMm8nNU26OKFPuLh/W2PY1lmMoA0/Qw7yMWdw6aQnejKn465t7JT0Ak2asZML3lxP0+yAYZP8nP4Vn3d+gP/otlKbTsH0HibW1NG/4V1zX30BcVjbxuaFbq6ZpsmvLVrx2G6Vv/Ib2HA1PoZ//6ZhN9mQb8xY7qS/1ULr//zFr7nxSMrMp/fA9AObfcDPxyal9vgZX2gQO+7MxTRNTKVR8BqeqKnjpg+MopXjyq90rzc9d8SkCfh8ndr0JQ5H42OMhpwQaT0BDGZzeCc5k8LXC3M9eev1CjEGS+IgwpRRVVS/hdE7o62jnvxoftvhJSB5s58lsACoaW8N7PmppYyWxk/j0NVrtYpxxiVx+403sevd10rL6en+Hj88weWbPD0iyJ4d2hPtzh0azOSwOHBYH71e93yvxcQUTeWPbe0R2Vur7udbZdhRKaDUc1OJ0NqOhoaN1DprrLNO5b01nLLquoRkN+E6+Tqu3jZq95aTWlWOxWDofOp72doJ+f+i6Ksj7dX5eu/1z/Ojza0lJSApV9Mmbw/9/9m7fxe6tO1l85eXh1+vx+Zl2661Uf/e7TLr1G1y+6kr+XikqWpu47633mJNsZ1dHAmkfl6IH9qMnJZOpK6pf/g05Eyf1fPvCyirPcLwywOSJeaSe8ZMZn4NuPUNCzkRs8Qm8tfsYFj3UQd+783km290kJOdSteWXl/B/NZLuc2M5eQCfNRFXgo+04iuHrG4hxhpJfESYafpwuYpITV16wXKu1je4Oj1pyK67/2TTkNU1Ii7hTpXd4bx4oSGWmZDH7VkrKEqdMeBzF+nLuXr+sosXVAqFCrV4dI6MO7PpHSZd/YnQeLbOKQnCxzVQykSp0Hg3pRRooeMpKObOSUE3wQwGMQwDIxAg0ZWAIyGRoGFwouoo2Y01/INF7056gEAgyKHdH9NSVUVKbg4LOpMegD2b3iNu0iS8Xi+5/+t/0VpXC4QStSP17fxqxXIyB3G7te+u16G9Pn+As81t4WQs/tPfICNleBbv9fv9HDlyhLySEpAZpYU4L0l8RJhperBYLjwyC6A9GCRoKqz60PRVaW1pwd0cmicoPMycyKHp4fl3tITQvDh6aKeudR7UO8/qnIvn3KHtuqaF910K0zQHO6qc4/s/ICEl5ZJjGCi7JR5vwD24kzUNu3NwfyYcNgdOV/rFC17EoeoT1NSfRimTgGkQZ7GSnZ7HdfOujihnmiYfXns9+s03s+LrD0cc+9P3/oP0mcWkFBYQ57Azb3lkch8I+HF0tYgNIYfdxqSsvm+RDRWlFA0NDZw6dYqZM2cOa58sIcYCSXxEmGF40PuR+CTbE/jjkZ/xqeK7sOiWS77uNcZWqo5P69F1pmuGQa3nFrYjO6gr+iymxUaoEUGBSWcLQ+e26nE63ZMclp9t5cufn3vJsXZ4glgHkfjs+3AjNpuLyQtLLjmGgdJbEzh8rIaKhPcGfO5gbuuFDUFe3NHexOFTh1h72Y1wkZ81pRSeO+7kmr9Zh2EY7H5/G2e3bmP5PXdhMU0wTTRdp6m2jjee/RnX33d3+FwjEAhP2BkL/H4/lZWVGIYBQEZGBgsXjo7RgkKMdpL4iDDD6MCiXzzxWTlpJbvrJ1DdcpSJqTMv+brOjFyKF15z0XK+oMHUuelo8QP/Zr5vXw2vbjyO3W7BGWejZFo6Kal9v9YPt1bS7gn0ecw0FXGDGJFfvOhqGqorOLzzfZTZPZFiuJtMV78bQv1ulFIoQ5EzeQZZEy6tT5DRHuSmlVcRN4j37VIMNu9RRhB3awOJrkRc8anMyprIm/s3Y9UtzMktIjMjv8/zdF2n42wt237/R1qa3WRPn8b8z97O4Z27seXmEPB00FR2kpyFCyiaPZW9v1iHv+gatLK3Sfcpqt8zmfDFn2BPGN4WmsEKBoOUl5djmiY2m42CggKsVvkTLsRAyW+NAMAwvLjdH5OT86l+lbdrOsEhuna/PyA1C5jGoK4xd24OcwHTb9DR7ueFP5dSNDGpO4DOpSqsukbZGTd/d8f5W4eOv1E+4OvbHVZyC6eQWzil3+copag8vpt975eCruGMczJhSjHxSQP7YPZ7vDjiEgcactTUnN7PVncHaRadVk8rl00qZubk+fx5x595cd8H3DlnGZmZBb3O+/3x36NPycRvmJg+H0vWrAJgYtFkANo7PMS7upPdZu8XsXubmfrZH/LqniMsXbYUu2V03iZqaWmhqqqKqVOnYrPZoh2OEDFNEh8BgGl6CXWU6d8ffgsmQTVU89H093aKBdTgEp8uut1Cgj2O+/5mfvetMQh1vjUVhqm4YpQsvaRpGpOmLWLStNC2p83NmROH8Lb76Os9UyjiXElMLlmApecHuEZU+n0M9m1sC/hZPGkWk5JT+fnWv3KioZrs9IksKFrA4zsPcl1Ha59jAG+fdjtMg4A/wLHde3sd75n0AMyd170kRmJSEp5gELtldN7uamtrIzc3V5IeIYaAJD4CAJsthdTUpbS1HSEx8eK3r6wWC0Gj99pcg9PPBErTLznxiaguvChpKAbN0t+0LzriEpKYOvfyC5ZxN1VzcNsmUJCQksyk4rlRW0NzsGlxm99HuiOUpDR3tPJGWxvFWRP43aGP+DtXkKm50y54vs1uY9blA5tZO97lorm9nWTH6Ex8JkyYwMGDB0lKSpLOy0JcIkl8RJjNloLHe6ZfZa2aFZ85VDe7+knXB32ra0hFYebl/kpKzWXu8lwAWhpqKN31AWdPBijpx4j00aLdUCR0djT+4qKr2VF+gNcP72DlxCnML5o3LNfMSE7mbGMTBWmjs38PwLRp0zh+/DjTp0+PdihCxDRJfESYptlRZv9acey6lUPNxzCxomlWXDYXU5InDuq6Vn/rxQsBmt2G8gWivxb2pYx0GkHJ6Tkkp+fgaTgZ7VAGJADYO1s1MlKyuWl+NioYQGnD19KRaLdSa47udeTsdjvmKI9RiFggbaYizOs9jd3evxmUc+OzmZe9lBR7HElWKK1+a9DXNa39m9RPc9oxvUN1e238iI00rVvACFLXVB2xT7Pa0C2XPnXC+egWC2oUJxXBYJADBw4wceLgvlwIIbpJi88Y9IO3jzE3P+W8x5VS4Q/DBIeVkrxk4uwWLNYEgr6afl1D13UmJnX/ET7edOKi5wRMxftnmrDpGldO6L6loPT+ddjU45wY7d5+lR1O1rObqdh4HBiSqWqGXbAqCEwe0Wv2/BkbqFl5RRw4fYyrU3OHNKYLUZqOZo7OFLGyspL29nZmzpwZXqVeCDF4kviMQXPzU/q96GerN8Deyma8QQOlfGienWAZ+K2RPc2NHGyo6ONIaJIaE4WOxuLsRDxBk6c+PEGcPbQy+PTmDvrTc0NPn0Bgxy/w1568yO2mHhPjnMvuQM/Jx5I3Gc05uAVDc+PbcFy7ZlDnRsXGwbfGDZoafFeoo2cruHr2iqGN5yKUpoEaPS0+Pp+PU6dOYRgGEyZMID+/77mLhBADJ4nPOJfotLFsSs9lBe4aVD1XX7xIhNUF3dfct2lnv87R4hNxfvqrA7wSGHUNGGdOoJme0NpQLW0YVe+hBT29cyQFZnMDtqXXYsnrPVcMgJaeN+AYxpsLpJ4XpaGhjfDIJRPQotx3yzRNTp8+jcfjwW63U1RUJC08QgwDSXzEKDC8N4xUUznq8BswYQ5aUjrmkc2ohjLMgIk+cXboi37tQTTTgEAHluV/g56RE7V4xwTTHNWj387l8/txOBxRuXZjYyN1dXXous6ECRNwuVxRiUOI8UISHxF1w/092zp9EdbpizBqTmPWVmFduQ5L7kTMpkYC77yAdnozKm02JKajsGG97Ea0C83gGyOjurp4PCN7vZZ922mqbsWZPLhbidHQ0dGBK+7iy7UMJbfbzZkzZ0hNTWXGjBkjem0hxjNJfGJMs7eZ3bW7cVh6fzvt6k66q7aRQ83W8Ad0YU0i6Yn96COgaZyt3ItKTxrSmCMuQe9Ep7Kjkcb9m/t1fte5F2tLMIwmFljKe5VUgO/DesygQnMmoGXmoxWuwzyxF9yH0EwP7EzhuHcGBqlYdK37oWlYLRpZTR5iaWyNbmunqnx/aEPrvJWkhTegx7amaXQ0ebFYktA0DU3TQzM/a1qoBUfTQs87V7oPlQk9dIuOputUH6tj6qoFaLpOsOUsmq6j6ZZQOV0n/P8kYsGyrm2NQDCIx9vePan2sL9DUNXYwOyMFHztLT3mtNR6Rnfh7Yjneuej8/3rvHXX4fFQVVWFaZpomkZ8fDwzZ176WndCiIGRxCdGNHob2VO7hxRHClfnXx2adbgP3qCXJWlgj+seIr5v9w7qt+0kvsHKhC/MZ+LkovNep/y1WgpvXDLk8V/IizuTuXrOoiGts6ajiberk/nslD56H/W1DNei24DQaKSqhtNQtY+riudhKBPTgKBpYpqKgKEob7bGVOKTkH0cq2NOaEN1rVjftYx9aGX7UHahME2oPPF78iZ+Bt3qBDOIIrScR9f5plKhJT5UZ31KoZTCNE2UMlGpqdQd3oEyQ/uVaYTmn+m6UDiTUb1bz5TCOHWcvc7Q7Z6uH/OeP+3DcQMtQwWh4iTnjmlUPWOlj3B77Az/t+s98TZDSxUE2kGBMyGJyTd9XfrtCBFlkvjEiFeOvcLdJXf3Snj2bP+QYDCI1vlxYLPYMC0KMxAk6AuQlJNO4bTpdLS14W/34tcvPNvyaO+V8XHdEU62N+DUbcxNyyc3PqfPJDDHlYpjEOsuaZpGbUs59S0nsNkt2Oj9IVVtj60PLrvNSnru+ZPdc6XnPkLpnhcoWXjPMEZ1Aa/+F4UzY2iq6XO1N8DJzZA2H9I/DY7YWSBWiPFAEp8YsSxvGQ3eBjLiMgA4W1bJqZqTuBLiWTDvivOeV1l+gmP792O12gjqfio/PkpRweia8n4gyVZ5ewOfKlxOe6CNvQ3l7KgvCyd9Xbq+lKfY+t9n44PDm/EH3J0VmBTmLhxAVGOL1RrX3cIjBk7TICkP8hZEOxIhRB8k8YkR01Kmsad2TzjxqXZXMXXaTFKzLjxfT35hEfmF/f+2X1F1iqq3W8KtKN39QcCVmETJ4oEt/tgfg2llirclsDynZMhi8HjOYrF2JkqajsN6/pE1sZYSDHQqwebaKvZvTKZkqTrvLdVhNdqbHS/GlQYdjdBaA4kXGh0ohIgGSXxihN1iJ2AGwtuFhVM59NFuHMkuFi1ZPmTXSZ1cyIzlnf1BUJg9+nZse3d4JsIb0MfyME0yt2bhZyO23933Z6Dvb+xajKU+QbNjQOVTsydQMC+RHX/chqaHOkCH+uuEjof6OGuk5KQwfUnxMEQ8BhTfBBVb4cxumHYtWPo3O7kQYvhdUuLz1FNP8eijj/Lggw/y9NNPA7Bq1So2b44coXPffffxk5/8pM86AoEAjz32GK+++ionTpwgOTmZNWvW8NRTT5GX1z1RXGFhIRUVkTMDb9iwgW9+85uX8hJiSnugnYARwGaxkZKazhXXXsvOdzehTBX6gBoCFt2C/TzzmVit0f/jXVF/lndb/xzaCCdBA3ztmhbZS1UDvXNEU9cOj7f5EiMdPRqa46nb/z+dW+d/r1SP96TDgGtvu+m8ZSs/PsGBl0uJ9wVIX1CEI94FSlG99zD+6jbQINDqZdrnVg484FG8ZtaAFCyDoA+OvQnFN0c7GiFEp0EnPjt37uTZZ59l7tzeQ2TuuecennzyyfD2hSbk6ujoYPfu3XzrW99i3rx5NDU18eCDD3Lrrbfy0UcfRZR98sknueee7g6XiYnjq9PgNfnXsOn0poih7GeTajj2h//iFqy45i1BSw7dCguNLAmNpNESktDj+/tenf+DMT0riw/eeC283bPdI1B5mokaF15IUtNQqvP2SeeHrKlM0JxwWf9GdVmdl7NgejYpjqFLwpRSmCo0c65CoaHQL7gSeGzdi3GQx9Q5nxnQOe9V7mHvh6V4O/ydA7FURF8qBTgK00menkf9zuMYXh8KSJ8+icSFswE4vWkvJ/+6DT3eRsbcIuLTUvu8Vnt9E3U7jmJ1OZi4aj6M8KzNw0vrPRRMCBFVg0p82traWLduHT/96U/5zne+0+u4y+UiJ6d/97aTk5PZuHFjxL5nnnmGJUuWcOrUKSZNmhTen5iY2O96xyKbxca1BddimAYWvTPBmAhqgSL4wW/R9v8SZUmkvbkZ09RwzboR3R6HeWgLWu65E6SdOyNOaJEBa6sOzO/z+jMXnD85Of7731Nwww3Y+pgEzltXTsvB91HKAK1rWLCJ8vjBVDT5HHy/PDSQWEfD0hmSUqGlBEDR1QbQ7tB44WgN988ZurWLNC10zfB7Kli8aiaBQJD4hDgs1r7fl0Ob9pKQnU5Cdnqfxyeumg+At6GVxgMVVFXsJW1ZEamT88FvYiqT1soazry+l1n330x7TQPHfrMZi2sMJAqmCeXvga8Vpl8f7WiEED0MKvG5//77ufnmm1mzZk2fic8LL7zAr371K3JycvjEJz7Bt771rQFNw97SEupcm5KSErH/qaee4l/+5V+YNGkSd955J+vXr8dq7fsl+Hw+fD5feNvtdvf7+iPlzYM12K06yXE25uennL8jaVfriGmG55wzTQMg/C3cuvzTwKcBaNy3hxSjmsaz+8m+7ivY5vV/aHDCll8O6rWoQADdHho+7nfX0bDtj5jeDtA07Om5pC28AU2zEnoBFjQ09DgnmsVC8cnXuaYwlNAaShFUCo2u20+gQ/i9afcb/PzA6UHFOG4NooEqLt7JxcfE9S9BcaYnkreiBNM0qd9xjOMfbcGe4QJ04tISmfXVW9B1ncSJWdiud9Hwx8aBBzzaHN8Iky4HZ3K0IxFCnGPAic9LL73E7t272bmz74Ul77zzTgoKCsjLy2Pfvn088sgjlJaW8sorr/Srfq/XyyOPPMIdd9xBUlL3DMJf+9rXWLhwIWlpaXz44Yc8+uijVFdX8+///u991rNhwwaeeOKJgb68EdXhN7hudg4n6trYcqw+3Mei60P+yKH93DvbCCU3GpRufgPTnkLCvFB/gT5H6yhFvF0RqD5LsMNN/Qe/JWvlF4Yl/oaGYzQ1HSIQCOCu+ADXq2dBKSzxSWRc+Vlsrv7OAN39OixaaIbk8/EYBt6AyX98VA7AuUPZe6pr9/EvK0fX0P2xov5oNe3NbQM6R9d1si6fQdbl51+ewZmcQHr+8M0cPmIcSdD55UQIMboMKPGprKzkwQcfZOPGjTidzj7L3HvvveHnc+bMITc3l9WrV1NWVsaUKVMuWH8gEOCzn/0sSil+/OMfRxx7+OGHw8/nzp2L3W7nvvvuY8OGDX0uLvjoo49GnON2u8nPH7rbI0MhNT7UQlKUmUBRZkLEseOH92BLV2jTrg3vmzl1De6T+2nd+xfSl30aZ8608DEjGKT12FlaT55Cq9lE6rqHsNidAxqO7K6vRg2gY+mJE28zY8YdOBxObP/f7eiD7JsxkBsbGXF2bpySydvl9ZgKNK1rHXBFsLGa1Rm14bKlLW72bdrX4yKKlPQsvJZEfE1VqIA3vGTDuTF0tLeyhxkYndMH0HkVXdNIrjf6nPx5PMmYnsuZU9Lydl75S+DoG6HRXUKIUWVAic+uXbuora1l4cLuyd0Mw2DLli0888wz+Hy+XtOxL126FIDjx49fMPHpSnoqKip45513Ilp7+rJ06VKCwSDl5eV9LvDncDiittpyf6kLdHr0tjbiCwTZ/O6bKMCmwxVXrSFp8hwSC0uo2fQr2PM6GVetw5aQRsUfdhA/K5O05TOxHAgS/PBDvGebsBcXYs2fhJ6edd5r7dq9icyGUlzJ6aRd/hle2/8abk/krUFTmREdfu26HXf7NtrOutA0Hd2wMNHIC69PpGk6CjirbFitFnRND63n1Ln2k6bp4ZFUrR39H279r9tOkBln54FFBaE1o3rY/O5R5i38ZHh73jlzEJqmovpsFRlGG4lTr8HmOP/t1z//+Xf8/c1LO9eW6hY0TLZsLut3vGOZ7Ty3mQWgW2QIuxCj1ID+cq1evZr9+/dH7LvrrrsoLi7mkUce6XMNmr179wKQm5t73nq7kp5jx47x7rvvkp7ed2fJc+vVdZ2srPN/oMeykiWrI7bP1lTx7Asv8qW1t+F0xZN79RcxPK3UbX0ZvG5SZn0K98ka3PuryFk2k8RJWZjuFpTPi2/vPuJWr+nzOnv3/BV7XCqbc1aioXhn07/y/y38ErOzLjzpobvDjd16A4byoTD5046NLJo/t3OEuYkyTSqqWznb4GHhzFRMpUIdmpXCME1Ca0SF1n0qber/ytQW4Mvz+l4pS3kv3I9L1zUm5E7o13USExJ7JT0AVouOZYimDhgpw9dVOLbehxFnGqFOzmNqlJoQsW9AiU9iYiIlJZGz5cbHx5Oenk5JSQllZWW8+OKL3HTTTaSnp7Nv3z7Wr1/PihUrIoa9FxcXs2HDBm677TYCgQCf/vSn2b17N3/5y18wDIOamtAIn7S0NOx2O1u3bmX79u1cffXVJCYmsnXrVtavX88XvvAFUlP7HiIbC1x2K5tKQ7dmFJCZ4GBqVgJOW2QCWX7azZ8+aCRVS+fs+x+ec/sqn0B7DZVb30bLnUPHvjMU3hrqzKwnJQPJPFe5n5LOlqP29lYKi2Ywe1bn/0cVZM7MK+iasvDO2Y/z/469y9v1R5kYn8ntBX2P5EoK998JdYF1WhKJT4z8f9F8IsiCKZnkZ1x4KL2zuvyCx3u64J04Z+9WQqUUyjAh0I67tZVmt5vWtnaamxsJGApLeAhZ5wmdm9kZGb3qilXDlZ6oYZpMcsyYfBUc+B3M/pS0/ggxigxpW7Xdbuett97i6aefpr29nfz8fNauXctjjz0WUa60tJSWlhYAzpw5w5/+9CcA5s+fH1Hu3XffZdWqVTgcDl566SUef/xxfD4fkydPZv369RF9eGJF1fFmWhu8xCXYyAYccQ4y8hPQLRpnatv5cGcVvoCJI9OBbgndLtpzuJ6p2QncuurG89ZbaJiYQYMaZzan3zmN0RZgymeno2ka9qRsrlo5G13XUabJps0bqa05g6ZplHdEDl7XdZ2vzAi1Nv209F1+ePhNNDQUio5aD1Nt9j47VZ9qPE1zq5uUxO7ko67Fy6LZF15SY6CcF1ggNM7hYNO7b/bar2ugrE6SE1ykJMSTl5ND8ay52OwDX8Q0Fg3XNDIedwetFQ0k5KWi2cZ4q4a7GgIdvSa+DD/RNND03s8nLYP9v4X5d458zEKIPl1y4rNp06bw8/z8/F6zNvelZ9+WwsLCC/Z1AVi4cCHbtm0bdIyjilIEfAZ501JITHPibQ9QU9aCaSgc8TYuL8lG06D+dBtlLR62NLYyuziV9rYgv9pVSWa8gzXTM7Cc03xusehYLDp5V07g1BsVJE7tHh5v6ajh11vM8Pvc1JZMigLl9lAdtHCkrAEI9YEJBkxsDguYiuX6HJTWPXrs9611xE3LwBM00YImmYkO7BYNi0UnP8eg4oyfU1o9Fl3HbtM5Wt/K1DYPlg4NDQ2rFhq1ZdV1LDrYdA1d02js8NLq8XS+ktA4LU3rXiOsawg/gNcf4OCZZiB060rXQg9Ng8xpi9A1wttdx3Q9NFLMoocSO10Dv9II+o0e5brPi8r6VMPIHKYFR+fccBk1J89w7K2jLLxxCFdT97UOXV1D5d3vQsFyuua76qY6JwtVncdUZ7OkCr2O9jpILYxCwEKI85HeiUPgbLkbX3vg4gUJ/WlMSndybOdZ5q3OxxlvY2JxWq9y+TPTyAeW+Qz+62d/4Zq1VzAzO5MzjR28tOcMKEhz2riyKI1EV2TLheENkjEv1NISDAYpSXexZNW88PHyD48AkLp4On5NI2gNnd/z816j80tr5x/5TSfqccZZcDd7mJbmYsbUDKqbvQQNk4Bh8uKJOu4syAwlT4ZJmyfA8SSdilYvSkGwc3ZkQ6nOBwSViVLgbTzJ+/vcoQ+Pztmdu9+vyA/tjH176Ui6mu+9XU5mUjxxditXzJoY/uwJ9SUKnReajTnUj8js41jonNAVusp1Xa22ooxZk3N7TTEAoJ9sxM8f+vz/W9/RwvvWE0xIHdqWrkthVu0icYt3WOq2AYlqD9X7mrpbQ3r+IPW1r0/d9xo99VvI+nXlEEd6aazBRJzz7+hfYW8LnNoemjl9+vWQ2f8+bEKI4SeJzxDwtgcomH3xDtk9TepneYfDwsJpRZysb6CqqZnVxdNYlxYajXS21csrH+4n/3cvULi8szN0YxPmnr24p/w9qQunYLFYSM9M58A7u9B1HZ+7DWPbaVKXTaKppbszsEYoCbAmxJF7xSws54zY+Wxa9wzaz753HLffYOXs7lm0s882UzKt+zX5DZMS/Nwy+eIJwItt1dx4niUr3E2NfPDnP5CYnoERCODKSueykhn8uiT0YfLfb++hrqaaK2flM6tg6Gb1/t27LaztkSz2dAgT+6q+FzBtKN3NyrRryc7M6/N4NBwwnibv8r8Ztvob9jWRPnfohm2fbionYeU/DFl9Q8Hzh//oX8GOxtCMzTNv7UeyJ4SIBkl8hoC3rX+tPYOlATfNLuZAdQ0v7dyNRddJPnoUm64zd2I+iV+7j6KZM/BVVNPyx02k//gpdJtO5c6XsDoScdnBlRGqyZdUh3mdnYqP/0Du0suZvuS2iPl32uuaOPXaTrxHjpAxYSLWrvmaerTwfxbYXGeDHonPuX/iS+vaKK1t46Xdp0O3koD8FCdLJ/dO+KqOVrC9yt1rMkKF4uihHWROm4/mzMTqBHvjWUp//evOa2osQXGq1c+mM3VUpvWea7izEQmlaWCxolstoOtYbFY03UJLIA6LzR6+tWbRdTQNPJ7B/T89Xn+MlrZmTp453vm51zm8v3MW6qT4FKYXzRpU3YN1oUkeRX/183Zh+fuS9AgxykniMwTiEkZmxEZJbg4luTkopTiTlEDTwYOo2io6zp7hcNkx8lKcOBpextgVTzDgx6V2kDTja2gWO6YGWF2cPv08RQsfpGjVHdRVHeDQR/8FQHx8LgXFNxKfmcrkTywjuGY+x37/MsFmL0U33UJ8TuR0BNZ33+dsSyuJCfG0+gKcaYm8lZLrsHFbfALXLpyIYZiYwMt7q0hztXK0vj18ByTdZSN16iKWLi0AIOjxUvHSG2i20PIWmfkl0BHAHtdBzjWLOfWb0xT97ecwTZOgz8POj/6E1t5GiVOxcN6NJPRxiynQ0srxv+xEU16UYaCCBp5WD1YLLLh1OY7sdDBDt8KCpkKZiv3b6wb1/+gTS9fi83tDH5OdfWsUJsFggLc+eo0ZE86f9HR42jhw4iMqG05iKIPbrvgbbLbx0QE7UowmDQFPaIkKSXqEGNUk8Rki4VXHh6Puc7Y1TWPitKlMnDY1vM/X1kbF9u202KaT7PMwecE1OBp1fNVbUaaf04d+R2ucC5cridOVPyS0AhakdJ7f0byH7WUvoAVdZDtuw5maSs6iy0ieMpWyP75Ca3UVM277NPETQnPoXH3ZfA7s2U91VS2HT5wlY+EK/vPtY+F4ggGD/HYfH/3lJIFAAE3T6Gj2s+WQzrJ5U5g4LXTrrNbtY+K2GtonhTpYn/7dRgq/eAuO5MiZrNur6qn80xb2HXqFo6+fpsPwk+5MJj9/NkXTl9DaXMfuj1+npbWOnNRJlBRfS93u47SfbUFpOtM/swKrvf8/7uFh7gNktVqxWiNjP3byMEcrD3PrlZ/B4XTS4Wlj/4mdVDaUR5Rz2J3MmrSARTOv4sDpPRw9vofZM5cOKo6R0HjwJyjTi8WeEu1QRgdldnWME0KMYpL4DAGr3ULFgQZ0XevRRbObIvQlcOKMVHTLIJd1UIry8ndxONPIyZ7ba3kIR0IC01evxlixgp1f+hJ64YdkzchHdzpxrV6L9ySkOibiaXLTtQSkw+Ui/7LLcKVFdq5urTxFwN3CgddeZflXH2Ta2s9yZssmqrZ9yLS1nw2d63ASrDjLpNQUPvXoJzlXIBDgh//0j6TdspI5cy4nKy2PyzuP7f/F/6GjugANjUSrleJ3f8PZPaH+NM54F+2vvUd76EVH1JmsaTgzC2lJS8em2zgT6OD9nS9j3fNHZs3OxZJlwZLl5EjjQSr/283SNcuYee35V5S/kEtNYTv2HcWz9whvn3mLkzNTmZJawJ+3vxhatNXqYHbhQi6bufK8y3wk2hKoN2suMYqQQ60GZ/dvDr+mnuOSzv15VUC8UcZUvfWcN0FFngB4208wYdl/DkmMY4I9HpQRWqpiwmKIH1i/PyHEyJDEZwjkTUu5aJm6ylY8bQHikwe+jIYGVFVtp67uODk5c9mz5zmsVge6bsNmi0PTraSnFZOcPAmbzcblL7yA+/Rpyn/3O6Z8+pP4PnyNrDOnaE91El5hzenEkphIxY4dBDweUIraykqyCwrC161PSeO9N15FKUWgooKCKdM5unEjAa+X/bv2037tPBzxitKPN9PkbWVezhRSnAnMzs7HZrMR+NRS5s5axuFjH7HD/RZKmWiaTo5eTc713whfx69r2K++jeo9h8Gn8EH3EOGIT2aNTFscNyxZBUBHRwMnk3KYPbuPWamXw443/sqEkpkDfr8HyzQMOrbtx7P/CLbphdTWH2XhLXfw6dlL+7WOWUdrDX5/G8o0aa4/wcm2CuLPOtE0HYtmQdct6Gih55qlcxi+BatuJSO+4LzXqClYxmem92+4+baaA6Q6JpGeOnlAr31oDd9c04PWeALPH57m/Clxj3RSKfStfwSri+CUz+BavAhNlvcQYtSQ38YRYrHqmMbg/qC7W7cSDC5gyZLQArCTJoXaTgwjiM/XgWkGqK8/SHX1DqzWOGbO/BRJEycy8cYbaTlTTd4nvsy5q1IF29pwHz1K3YkT+HUrCz7/Web2+OA8daKKprc2csW8ZWTmptFYXYXNVGgWC/EZGZQm+7hh4SoMZRI0TZIdcWytLOVEYzVvl+3GarFgNYJkpuaSueQTEdc+sK0xYttb1ozXrKB1TyUTvrg4tDM0mU+P/hKhJOho/fHweX5/oM/bi2fKSqk9fYqJ0y+87MaF+Py+8x4LHjpCY3U13YGqzludOnHzZ2K5cjZnN73L9Ae+isXe/0T30Ef/RUbOUjRdI81mY0F+MVbNwFQBTNMgGDRRKAwVxFAmpmliKoPKlqPMyr6CGVlX9Flvfzs3m6bJibZ6Ls8puXjhYTX6Ep+4Lw+uZcvW3k7rxo0k3Xj+yUeFECNLEp8RYrFqGMHBTfGflzedgoLLetdpseLqXDoiIWEFAHv/539Tui/0oa0CAeJ7tOD0ZE1I4Gh9Ey3NbbiKi/nVto+4YloRZZsOk5QWT0e7h7+9+4uU7jvJsYPlKMBqtVA8dwoWux1/cz0Nx3YzZe5V4TqvLpoTfu4N+Pnzzrt593ATLkc6iws/T9Dwhebl8bdHxOKckoL96gLaE9o5s/FjUudNIq24gCP/8Rrxs7OB7u/Z1o7uRKKt7UzEQrQeTzX7d/4cw5tNSkY2LU1ltDQNbkFRi3sfxzaHVh/Xur/IA5AW3E3aHf/W53k1m97FW1fLjAe+NuBrOlwJdLSe6t7hhmDnU4+njkUrv9nneVM6qth47L/ZcvIVPjtzfWdLmYlSBkqZNHn8GKbZa9LLc71+eifXThgN686Pnc7Benw8pseL6fGgx/UedSiEGHmS+IwQ3aIT8BqDO3kAX4CTmxpxTs5AqSBBU3G4oYZTr3Yu42CGWgn0zsVkLQ471z/wFQCuAt48fJQzKSbu5gYmpqTT0tDKrAVTwnX7/QEO7ynjwO6jJFQloxdZ2Pa7H4KCpNxJFC+7mcONh9l8ejM6OpnOiSwp+lu8wVbeP/YsVkscGhoT9Fa81Vtx5oZuv6jOBbiyLyvG3xTH2TcrKP2gjOTWAFanjYlXd8+Zs/P3/8Mft/0RAE97M7bEGo769wMaWttOrrvyWXT90n6slbeVrLjTpM/8TJ/H22p6970xDYOK3/8O3WKh8DOfG9R15yx96LzHDu342XmPpbry+Oy8R6je+a9UntoS6mCraXQNpTdOWPmhdiY8WWPPVjJTKT43NYtUh8IT9JMZ13syTXFpkm/9BG2bN5O4evXFCwshhp0kPiPEYtXxGoOc72cAX4CzbvwSzglFWOwuTrWeBfdZlvfzW/x1M6cTnDGVrScrONXQxN73dpE+eQaX5SQyOTcRu93GvKXFAJT+up3JJVcwuSR0e+Xgjtf569+sQf3z1/jK3K+g6zqHq99h3+k/EjBCLTxeXyNFOasomHoXje/8IwE9F1daHsc/OEH73rdwpSYw9fb5FNwwmSN/OE7eLaF5gtyn20JvgwYpqcmsubzvyfKO1c5mc+kzFKTNx2FLwKo7sVnjsOpOrBYHTltav/ramP5mglocwWAAXdNDc/z0OM/0+QHwNTZSs2UT/oZ6MBV5199A/KS+W9hGQrzFQW5J79mF68++ycq5+X2eEzRMfl5aTWXDNv5p2S3DHeK4ZLjdWJKTox2GEKKTpi62UNYY4Xa7SU5OpqWlhaSk3qt4DzcjYFJxoAGrfeCjuvxGGakTBr7kgLvVw+6zk0iI6/6j29eos3MpAKUobz/Ece9+vI4CWj0GN9gdXD17GTnpWRz+f39CT04J15g2LZeO5HaqPt6KjoYyDSYtuYa8SZHz1ry273EMj53JtklkW7PwNlSiWRzkXXknJ197lVPlrbjyJ+NrNfC0BM8JClrim/nMl3qPIuvS7m/mTMtxfME2goYPw/RhGF4MFaCueTefXPh/I8obfh9KGehWO7ol9D3gVFMlG49tY6orO7T6UmdLSY0XttRC1olyrJoVW30tlxdns/y2tdgdA++0PhAHdjyL3sf3lMaGj0my5JAXqMKWW0Tywt4L927e9CYrV113wfrfO/BXgkYw/PNh0e1MmzCPvLTBzUB96tirNNWewGa7+O0d1bnGlUZoUV5Vc4aSW/95UNcdrVrffZfEq6+OdhhCxKSh/vyWFp8RYrHpFC0Y7PpNgxsWm+htY9IsO5bEC0+CZ5omDftPkliQiS3B1WO5igk8/doeXBkNkAhVvla2n7ATPKLQSqyg2jCNIBM+9tFW00LOgkKW3d691MB7v/xX8v6mO/F5c8+bnKmZyILpC5g9JTTM3NNUQ8OJj9F0nfyVV+Do+E80dRo9KwXb9BziJpXgyu4eYfTSaz+84GuJt6cwPXNxn8fePlhNdfMh0uMncbi5nLOtJ6g6WEpqSytGYiIz80MjwE55A8yduAi3SmZ/bfeCmZkuO/+6OpPkm1cC8OK7e1m8aDI7Nr1NMGhQPGcu6Tk56Lre2UKkda5ZqTCN0MPX4eHI1oOhDsed2WdXEup0l5KZ4SFSKBXJBBSBzvLd31XS9ZkYnjYcc+8hcXLfS2z0x1UlNwOw8Z2teDweDMPHXw78nimZreQkDfzntr2tgkUr/xmLZeB/Yg7/6pcDPmc085YexZKSEu0whBCdJPEZw+pOncRf14Zms3SOPeoUMfLWREMjaWoetTuOEXB3YI13YAQMquvKWbNoFSVzlwDwTsU7fFT7EWmJafzd3L8DQvP1/OLQYyywL8XXHNlpOXP2It754dOcycojcaIdhSIvM49FU7rn1qnywattBrP3bw7tKA59KzaNIGbTGfLefpaSO58Kl0+wJQ76/VhZ/CAHq9/keN0H/HflKe6f9v9xMKWE5lRwWnRuX1gIwMHtp3jqzxXMzW3l3z9ZgqWzT1SXzfvKqGvpwBcwSExK5srrQ7fe9mz9gC1/3kdRYWh2bZQZXgpD00MPq8PGgusXY3eEZvtWpknDno8IdHhoC6aSc/3fDvr1DQWPx8OtN18T1RjGGqOpCduE0bN2mxDjnSQ+Y1jKzInU2I8Sn5xCztTpFy2fNj2yH8jWv+zg83O6O/heU3AN1xRcw7MfPxveZ7PZuPveDWx593nqvKcJHjSYPvtKqt/dheVYC0s+eQftmpWyIxVcsXphr2u2GLB8+iIW5mb3OhYI+Hls117m7dgV3nfIqzAq97I8czIZzoH1m7BabMybGGrZeO/UH/ioqoVab6gVZVFmd0I1My2Bp1fPZPOZpl5JD0BlnZtPX1WC9Zz+QguWLcfbto/F1/avT1XrsYPUHj5F9sJ5JKUkkz3Mt8v6I9jRFu0Qxpz4y5fi3rgRW3Y2mn08LkEixOgiic8YFp+SypRFSzl95CAn9+6KONbVAmSxWolPTSMxLR17XORsP7es+hteffcFPrHmwq0Quq6zavVdAGzf/md+8n/+lVuX38y0e9cCkAB4Orzsev8Ai66MnCOmIxDA2WOY71MnqrBqOtbQXSKWFE5lbU73SCOlFnK0tZG/Vp/EHfBgdva/mZuSw9VZky+6bEhdm5t/eus55iXOJNkdZFHXr0Cdh5c3hoa++4Mmt1xVwKYzjby4/RTp8XauL+lekFXXNZz2vtdn09BCI+f60Ym68Vg5U269+aLlRpLNlXDxQsPMvMAcSrEq4aqraN++g4Srrox2KEKMe9K5eZwLBgK0NzXQ2thA0BvqQN11J0wBOxt3kzcjcvbjzZWbWZm/Eg0NhcKm2+ho8dFQ7wbgpgVr2PXmSa66LfK80n0n+VP5HynMnYDqnPSv1mvQ5Ehn0ukmsjIK2Kt0SjCwdM7U3H2DTuE/eoS4iU4cEydi6WggzVtHMDGUkJxob+JEWyufr/gdZu5MWrOLw9c1PzyBZ/Is0MDn6cD90RnSLgvdUuuaTbonpULD64OGot0X5FRjB9NcBjVTZoAjjuozlVw2KalH+VCMmqbRcKad7LQ8dF3v7LQbSobcVSZpmZE/d4GaMqYUtHIkeBpLmtb5KiN/HbsmH+za3+ppZJI9NfyedJW60JwHvz2WSuakLIqaq4hLmnjecgC1x4+xZKKDd8giPSH1gmWHi23zJpIX9n+NsgNWB/mOS21JMelav27InDMBlHGmkms+u5Z4a+9WRCHE+Q3157ckPuKSKKUImkF2vVnO0humhltc/v2Fn5GaHU9DRyNFGYV4/F7i7E4qm84wf+IcVs67PKKejW/8hGuv/8p5r+PZ+BJGSwPxt/89mq6jjr8DSqFN62NulLeegDXfDm+6/98T6MmhViMVDBL0Qurd6wf0Onf/8IdMuekmkicPbimHrW/uY9l1oVtgHx8/TNnZk+EPxkAwwOdW3Nqvev7fvv/HvXPvHfD1W9tqqCnbyLR5X+xX+bf3b+aakhW9WtDqW3384VANFjRuKs4iO9l5nhpGzvfLa1hfmHPxglEWNBUfNLfhNU1WpyVh1cfORI1CDCcZ1SVGFU3TsFlszF1ewMn/v707j4+yuh89/nmemcxkEjLZE5IQIEDCHkCorCJIsLhUcftdkGrLpXK15feyrVZra+ttq9Xr7b2Ker3S1rXFarXWBRREUVnECIFAICwRAmQnJCF7ZnvO74+QgSELSZjJYr7v12uUPNuc831NnnznnPOcs/c04XE2ohMHce3s+Rz55jijh44mfUwqFc4KlFJM1cajoVHrrCXMcm5cTXVFFsXrnz//wt5vyq4TXxA/5z8ZtHCJd3fxCRfuI59j3pVN0tL7fAsV5NtlZ195LglShkHT+892uZ5pt95K/ltvMXHVqi6dt/fkXgqrCsms3U3Jl0UAGB6Dm2df06nuML/R9ObVwzup8LDi12VHuGZULCkRNoZENHdH6oYiMTyYK4ZF8UFuKSfrHPzyylGBKnWn9Jf0waxrzIgIZX15NY2GQZguLT9C9AZJfIRfhNgtjJgcS+GhSk5UVWAjnEkJkzhdVcXHb2aTmBJF0pQwb4/M1yVfMzluMoYyOFZ9DFJDsY4Yf/ZqzV039fVH8XgasZgV9eyiPifLmwzVNZ3ksCkKW0gSeZ997C2H2aTzHacDK3Bo5yc466tbrfK+p8JN7Bc7ztvS0exG5/aV22OY2MYRAPXFxZz497uYoqPZzTFMI5pnvK511PK99OsZHhyBqaGJurpKqhsq+XjD85h1M2jNcx6FhEQw84olgUuGNA2tC4nP/HA3t80eQdmZJvacrGL7sQqgORrzRkYTZgvi9qnJbMgt46ltx8ira0ILMfHM7FRMph5M6OiLK3u1VuVyk1XTAMD1seFYejLpFUL4kMRH+NWQMb5LHgwjmqlzWrcIJNuT2V60ncjgSC6Lu4zpCa3HdChlEB4+GdOwH6Hrvk88FYfnMu6yYEYl+C5E2tRQz/7t5eT9/S/Yg01ce+t/b3Xdz8OO84Npw7tct6cz69iSu4Xh0cMZGj/UZ5/H6SIsfSIVMW7cu7KIqjyNrunYXQ5yvnqX4QnjMEfGEjt0LOGRcc1Jz3mqygv4eMPzLLq24xalbvdMayaf+X9aNNRWUZKfS2NtJcNSJxIWNxyAxkYIsQWRYgsiJcF3CoEDxdWUVDtQSrGvvJaZCeGsmJqM3db2gO+BqsLpJqumHl3TiDSbmBcZJt1bQvQBkviIXjM7aXaH+yMiptHQkE9jUxHxcb6rW1uDLDjdzlbnBIeEMnXhUlLqnPyfTYdpe3GLbgp1QJCVrKKsVolPULAVt8PB5LEZTB7b9Rl6I2OTKarIp7G+Gk1B8CD/LHGglKKoppqswkMkH8pi7xl7y3ryzeW22YkdOpZjZS5O/r97uWzWNaAMjjaZGd3ONe/flc//npqCruksHh1P2uDuz630bVPmcLG3tgFd04gwm1gYbb/ok4ZCiJ4liY/os8zmMOz2dNzuWo4ffx7QCQtrflJMc9dz5PQoyhvL22wF0TSNtPgwPj98Cqfb4Orx5wa/dr7Dx1eQyUJqbConTp/gza/fZFDQIGalzmJv0V6aaqqxHMtjuFrQ7T90aUmTyPzq35yuLuLWm3990eOVUnx58iB5FUU0upzeZMbhcRJsDvZ28cWEhjE2Npkxt/5fzEG+LWdHjp3k0237mDXrOwxd+J53+4Z//CcN29YRpAdx+cipJMTHePfdHB3O7pIaYkMsLBoT1626fps0eAy+rq7DaSjirUGS7AjRx0niI/q8qKjZREX5tg5FR0Pq0HZOOOvKtOalFt7fW8wXR8q920+d6fq6Z800EiISuGNm85NRu07s4sujX5KemI4t0UZ55GA2bXgeXQ/idFUhS5b8vktXv+KqO3E21vPB+qe929yGm72n9pJTkYPD7eDowT2sO928pIPL42HzkULmJE3FjpngqGh0cxAYBsploBkeNAxMTTqnKstJmhRDZPi5xMfpNvh6z2GKjuQxdGgiSQnR3iUm5iVN5eY51+NwOfjyyC7W7d3AtekLSRocz12zU1BKsSO/kjf3FqGdzTsV0OjysHx67y3U2lPq3R521zTQaBjYdJ2ZEYOwyrgdIfoFSXzEt94Nk3yXC0hMCuNEo4Nhtq7NlKw7PZSXlzb/oBTDbEkMsyWhPAqj3kmUPZmoacl4DIMX3/4lzqIyNLMZTDpKc4Gp+TzOaw1QnP/z2bl69Cae2vEnPMpA1zTSItKYHzeXQUGhbC3WuX7Bnd7zr7/KjY6GbtKpPn2a6jPV6CYTmsmEJdhKcHAwHgUlJRXs2pNLbEwkx/NPomh+ymhaWiLzLh/Pe+s+Zfsnn5M6KZ0RKefN4G1onCwtYu+pfXyz5RtmDJlOg6ORotpiRsWMpKHhDBEh4VQ7agi3hnPEXQv0bOLjqK9nf3ExBhpuwEDDQMOsgcWkY9E0LLpOsNnE4A5WSXe6PDS53Oiajq41T1SpaxqapqFrUOhwktfY3L0aout8JzyU4B4eyC2EuHSS+IgBZ1SIlc8qa7uc+KSfGUFlUHPLkdYySNU70SJoSoECTWncOfU+mvJKwO0BQ1HiXkd4bOrZU7Tm7jlvwqOd919QTUVMZApB5iBQoKoVx2v2Axqm4ub10JRS7MnO5URBEdXlp4lLTuZk/gnSxqR6y1tYUMSd37+ZYwWl/OvPLzA4zEJ9fDxjpkxizKy5PnX7yT13kHfsJFlffo3JOspbtq/z9mA2m/hft/1PQq3N0wS88+WHNFY0Mig4lJtn+Y69Kjm4qUsx9YfEgjycttHoKIIAk1JoKNyGwmEo6pTCaSg2FxQzMcqOpsBaZcOaEImHcxN27q+sY0ZCBEopDEPhUQqlwF3rxHm6kVEzh7AgOky6sYTo52QCQzHgOA2DzDP1XBHVtUG5mbsKmT6t45mPAep3l2EKDcJT78I2IQbdYqJk73oSJrW9PMXuz1djPbtUhAaERY4gObXtAdJZH76Hq6mJXaVNXLVwHuNSm1tXSk+fAZeDwQnxKKVwOJ089fjTRMTGcc9Plvtc45MX/z+W4GAGj0qjuqyU+jNVTL1uMWHRzeN4nB4nH335Jjde0bnJDs/3/MFN/Hjswi6fdyne3bqVxVdccdHjahoa8Og61iAL5XsO0VRQReJ3RhM2JKbN45XLoOlIJaZwK5YhMoBbiN4iExgKcYmchqLC5WZzRU2rfS3fAtLDbMResB6XMuk0Hqpsbu25oMuqhdHgwjoiHHNEMJ4aJ86CWvAodFv7v2q6yUyIZbK3xcdTD8ezs3wePm/ZFzt0OEopTKZGxo4aSkV1AftOHqPm7GKrFOYAcOiDd5kxdjo2q4Wv3nnT5/0GRUZRkneY1MtnMWTsBIoPHyTz3//k8sW3YY+JxVVXQ27Ox4TU1xEbOYTxUxYSZOncDM0XLrnREzrb/mIPOTex5bBp41BTFXlvf4H12hlYQlvXrzG3AtuEGDSTtPAI8W0iiY8YcAaZTSyOb38dKo9S5NQ2sq+2kfM7o47EmJmaFElQJ+diMdktmOzNa0hVnzKoqNhKcHASdfWHMZtC8BhNREddQfK4iURHT+3UNfMLi3lxRy61Tjfv7/yUiEExTBkxjYjQUO8xxw68x6yV/4OYpAmd6pYZ9Z0Z7PtkA4e2byEkPIKmigpusS8kbdGdlBbn8emmv+LBQ/q4eSSnTPI51zAMDMPAbDafjVPPJwlKgWF48LhcOBxN1DfVUttYTXVdFTHWwQyKiCA8ItJbxhaaphGelkhT2RksIwY3d3E1unGfasBVWo9yG5L0CPEtJImPEBcwaRqT7SGtts+P7n4Ta4htGKGho6irO0RU5CyCgsJRyuDkyb9is13k8bTzVDSdZPnllQxLugazuXX3i+FxU/fyPzEmLqSaXed2nNejvanezcGkFPTQKFwKBgeBJe1qRtVWoTe6Mbvt/DgvmODHP2LVaBvHCuIZMSSGFz/8lNgplaCgvMJFRVkNTdUGDQbMmdP8WHt+XTCMvbBUgXVALyXo89fRzCZMQUGYTRb25ucSHhrB3GF2Ck+VcaS+Ho9h4HEbeGqdhLqsxMfE4KppAJML8h3Ns1tbTGjhZnLyD2FoBkMLFMnJyRcvhBCi35DER4geEBY2DgC7Pd27TdN0kpN/SHX17k5fZ9qoGSh1OcUlbxFs9V2Ys7o6m+DDQYx++E9YIxLavcZwt5uqNzcQfcMUquocNDo8hNmCCB/UPNjbVd9I7BN/4Y+3ZpCSOs47T9J31ZVoZx/ZPllcy0dfFXDG6uTO76aSEN/c4vTMruOdrou/hMcN4bq0md6f/7n1n6y65T4sZt8V26sLCyl4ZxdhtjDMQToh9U0ooMhxHJN+Nl5ujbLsUkampzF00kjOnDnDwYMHiYmJITY2tgdrJYQIFEl8hOhFum4hMnLGxQ88j6bpJCX+t1bb1Z4ydFtwh0kPgNlsxmQyoes60XZbq/1NSuf2uYtISU07+34tT7Cd6/aJi7ExJCaEM7VOtu4t9XZwmVvGGvWi8qpyn6TH3djI/vXrCQ4NZdyqG3zWQ6s5eZKg3FzGzL/Mu23c2f/nleZRWVeJyWKirLCM6pxqTJqJ8WPGM3zwcHm6S4h+ShIfIb4lrKZY9JBQXMXFYDKdXeGe5lXZjbPzVZvN6DYbyuNp9zomk4nI4I4f9S8tb8BqMbHqtnGEhpxLMj74qsAfVemS84dTK6UICWrupjQ8Hg599BHOpiYmXHcdZlvrJO/ojh1Muu02APYc38PR8qMoFKGWUL4u+JoJCROYkDQBm81GZFwkbsNNpVFJYVEhCoVZMzMlfgo2c+trCyH6JnmcXYhvCXdFBZ7qGjA8KI9BS0qg6bq3tUa53RiNjbhKqrGOPNvtdkHLhdvpYWt1PcExNjSaW3xabhMWk866T/KZMCyC+VMTSYhr7uKqKq3nzKlGCs0G7vjOPQHmL/XFLxCmKqhxNXGsrpIQfS7h1nCcBQVEAZZBLWOh1Nn/ttzyNI5VVRIxYgSapuFwObhjVvMj/Lvzd3P09FHGJY5jfNL4dt/b6XGSfSqbRncjEcERpMekS0uQEH7m77/fkvgIITrN6TY4lFnC8DFR1FY04XY2tySF2C3EDu2duW5crjPU1Ozlo6J9lDiauHPcna2SjyA9iMjgSHIrcqlqqgKaE6DksGQGhw5mW+G25vXNAJfhYl7yvFbv83TW04QEhWAoA11rPWNzjaOGyqZKfjD+B4yOam+JVyFEV0ni002S+AjhHw01TprqXIRFBxNkNfV2cXwcrjzs83NLAlTjqKHJ08SgoEFMjpvs3f9l0Ze4lZv0mHQigiMA2FK4heH24SgUSikUipf3v8zcIXPJGJZx0TJsLdxKemw64db2l8cQQnSev/9+X9JCM0888QSapvHTn/7Uu23evHloZ9e3aXndfffdHV5HKcVvf/tbEhISsNlsZGRkkJeX53NMZWUly5Ytw263ExERwYoVK6irq7uU4gshuiHEbiEqMbTPJT0Ao6NG+7zSItNIi0xj2uBpzEma45P0AMxKmsXcIXO9SQ/AtPhpaGjo6Jh0E18Vf8XY6LFttvJcyFAGtc5a7Bb5ciVEX9Xtwc07d+5kzZo1pKent9p311138fvfn1uZOiSk9Zwo53vyySd55plnePXVV0lJSeE3v/kN3/3ud8nNzSU4uLn5edmyZZSUlLBp0yZcLhfLly9n5cqVvP76692tghBCtBISFOIdIA0QFxrHlUOuxKxf/Ha56cQm5g+dL+N8hOjDupX41NXVsWzZMv7yl7/w6KOPttofEhLC4MGD2zizNaUUTz/9NA8//DA33ngjAK+99hrx8fG8++67LFmyhIMHD7JhwwZ27tzJtGnTAHj22We59tpr+dOf/kRiYmJHbyGEEN02K3EW24q2YTFZmmd3VgZjo8cSY/Nd42tr4Vamxk+VJ7yE6OO61dX1k5/8hOuuu46MjLb7u9euXUtMTAwTJkzgoYceoqGhod1r5efnU1pa6nOt8PBwpk+fzo4dOwDYsWMHERER3qQHICMjA13XyczMbPO6DoeDmpoan5cQQnSVzWwjNTKVIYOGMDtpNpcnXM7Hxz+mxlmDoZoHd+eU5zDUPrRVMiSE6Hu63OLzxhtvsHv3bnbu3Nnm/ttvv51hw4aRmJjIvn37ePDBBzl8+DDvvPNOm8eXlpYCEB8f77M9Pj7eu6+0tJS4uDjfgpvNREVFeY+50OOPP87vfve7LtVNCCHakjQoyftvq8nK4lGL2XNqD0V1RfzH6P+gylHFxNiJvVhCIURndSnxKSgo4N5772XTpk3esTcXWrlypfffEydOJCEhgQULFnD06FFGjhx5aaXtgoceeoif//zn3p9rampkzR0hhF+EBIUwO2k2ByoO8HnB59Q4a3B6nFhMloueK4ToXV1KfLKysjh16hSXXXZuenePx8OWLVt47rnncDgcmEy+T3pMnz4dgG+++abNxKdlLFBZWRkJCeem2i8rK2Py5MneY06dOuVzntvtprKyst2xRFarFau149lnhRDiUoyPHg/RvV0KIURXdGmMz4IFC8jJySE7O9v7mjZtGsuWLSM7O7tV0gOQnZ0N4JPUnC8lJYXBgwfz6aeferfV1NSQmZnJzJnNCw/OnDmTM2fOkJWV5T1m8+bNGIbhTayEEEIIIS6mSy0+YWFhTJgwwWdbaGgo0dHRTJgwgaNHj/L6669z7bXXEh0dzb59+/jZz37G3LlzfR57HzNmDI8//jg33XSTdx6gRx99lNTUVO/j7ImJiSxevBiAsWPHsmjRIu666y5eeOEFXC4Xq1atYsmSJfJElxBCCCE6za+LlFosFj755BOefvpp6uvrSU5O5pZbbuHhhx/2Oe7w4cNUV1d7f37ggQeor69n5cqVnDlzhjlz5rBhwwafcURr165l1apVLFiwAF3XueWWW3jmmWf8WXwhhBBCfMvJkhVCCCGE6LP61JIVQgghhBD9iSQ+QgghhBgwJPERQgghxIAhiY8QQgghBgxJfIQQQggxYEjiI4QQQogBQxIfIYQQQgwYkvgIIYQQYsCQxEcIIYQQA4YkPkIIIYQYMPy6Vldf1rIyR01NTS+XRAghhBCd1fJ3218rbA2YxKe2thaA5OTkXi6JEEIIIbqqtraW8PDwS77OgFmk1DAMiouLCQsLQ9O03i6O39TU1JCcnExBQYEsvtoGiU/HJD7tk9h0TOLTMYlP+7oaG6UUtbW1JCYmouuXPkJnwLT46LrOkCFDersYAWO32+WXqwMSn45JfNonsemYxKdjEp/2dSU2/mjpaSGDm4UQQggxYEjiI4QQQogBQxKffs5qtfLII49gtVp7uyh9ksSnYxKf9klsOibx6ZjEp329HZsBM7hZCCGEEEJafIQQQggxYEjiI4QQQogBQxIfIYQQQgwYkvgIIYQQYsCQxKcf2L17NwsXLiQiIoLo6GhWrlxJXV2dd39FRQWLFi0iMTERq9VKcnIyq1at6vS6ZA6Hg8mTJ6NpGtnZ2QGqRWAEIjbHjx9nxYoVpKSkYLPZGDlyJI888ghOp7MnquRXgfrsVFZWsmzZMux2OxEREaxYscLnuv3FxeKzd+9eli5dSnJyMjabjbFjx7J69eqLXvfIkSPceOONxMTEYLfbmTNnDp999lkgq+J3gYoNwPr165k+fTo2m43IyEgWL14coFoETiDjA/37vgyBiY+/7s2S+PRxxcXFZGRkMGrUKDIzM9mwYQMHDhzghz/8ofcYXde58cYbef/99zly5AivvPIKn3zyCXfffXen3uOBBx4gMTExQDUInEDF5tChQxiGwZo1azhw4ABPPfUUL7zwAr/61a96oFb+E8jPzrJlyzhw4ACbNm1i3bp1bNmyhZUrVwa4Rv7VmfhkZWURFxfH3//+dw4cOMCvf/1rHnroIZ577rkOr3399dfjdrvZvHkzWVlZTJo0ieuvv57S0tIA18o/Ahmbf/3rX9xxxx0sX76cvXv3sn37dm6//fYA18i/AhmfFv31vgyBi4/f7s1K9Glr1qxRcXFxyuPxeLft27dPASovL6/d81avXq2GDBly0et/+OGHasyYMerAgQMKUHv27PFHsXtEoGNzvieffFKlpKR0u6y9IVDxyc3NVYDauXOnd9tHH32kNE1TRUVF/il8D+hufH784x+r+fPnt7u/vLxcAWrLli3ebTU1NQpQmzZt8k/hAyxQsXG5XCopKUn99a9/9Wt5e1qg4tOiP9+XlQp8fM7XnXuztPj0cQ6HA4vF4rMwm81mA2Dbtm1tnlNcXMw777zDlVde2eG1y8rKuOuuu/jb3/5GSEiI/wrdQwIZmwtVV1cTFRXV/cL2gkDFZ8eOHURERDBt2jTvtoyMDHRdJzMz00+lD7zuxAcu/lmIjo5m9OjRvPbaa9TX1+N2u1mzZg1xcXFMnTrVfxUIoEDFZvfu3RQVFaHrOlOmTCEhIYFrrrmG/fv3+6/wPSBQ8YH+f1+GwMbHH+dIi08ft3//fmU2m9WTTz6pHA6HqqysVLfccosC1B//+EefY5csWaJsNpsC1Pe+9z3V2NjY7nUNw1CLFi1Sf/jDH5RSSuXn5/e7bxaBis2F8vLylN1uV3/+85/9XYWAClR8HnvsMZWWltZqe2xsrHr++ef9Xo9A6Up8Wmzfvl2ZzWa1cePGDq9dUFCgpk6dqjRNUyaTSSUkJKjdu3cHohoBEajY/OMf/1CAGjp0qHr77bfVrl271NKlS1V0dLSqqKgIVHX8LlDx+Tbcl5UK7O/W+bp7b5bEp5c8+OCDCujwdfDgQaWUUmvXrlXx8fHKZDIpi8Wi7r//fhUfH6+eeOIJn2uWlJSogwcPqvfee0+NGzdO3XPPPe2+/+rVq9Xs2bOV2+1WSvWtX7Dejs35CgsL1ciRI9WKFSv8Xs/u6u349PXEJxDxUUqpnJwcFRMT4/2j1B7DMNQNN9ygrrnmGrVt2zaVlZWl7rnnHpWUlKSKi4sDUufO6u3YrF27VgFqzZo13m1NTU0qJiZGvfDCC/6tbDf0dnz68n1Zqd6Pz/ku5d4sS1b0kvLycioqKjo8ZsSIEVgsFu/PZWVlhIaGomkadrudN954g9tuu63Nc7dt28YVV1xBcXExCQkJrfYvXryYDz74AE3TvNs8Hg8mk4lly5bx6quvdrNml663Y9OiuLiYefPmMWPGDF555RWfZtve1Nvxeemll7jvvvuoqqrybnO73QQHB/PWW29x0003dbNm/hGI+OTm5jJ//nx+9KMf8dhjj3V47U8//ZSrr76aqqoq7Ha7d3tqaiorVqzgl7/8ZTdrdul6OzafffYZV111FVu3bmXOnDne7dOnTycjI+Oi5wdab8enL9+Xoffj0+KS781dTpVEr3vxxRdVSEiIqqqqaveYL774QgEqPz+/zf0nTpxQOTk53tfGjRsVoN5++21VUFAQmIL3AH/ERqnmbxOpqalqyZIl3m9f3wb+iE/L4OZdu3Z5t23cuLHfDW5uS1vx2b9/v4qLi1O/+MUvOnWN999/X+m6rmpra322p6Wlqccee8yfxe1R/ohNdXW1slqtPoObnU6niouL82kF6o/8EZ9v631ZKf/ERyn/3Jsl8ekHnn32WZWVlaUOHz6snnvuOWWz2dTq1au9+9evX69eeukllZOTo/Lz89W6devU2LFj1ezZs73HZGZmqtGjR6vCwsI236OvNal2ViBiU1hYqEaNGqUWLFigCgsLVUlJiffV3wTqs7No0SI1ZcoUlZmZqbZt26ZSU1PV0qVLe7Ru/nCx+OTk5KjY2Fj1/e9/3+dzcOrUKe8xF8anvLxcRUdHq5tvvlllZ2erw4cPq/vvv18FBQWp7OzsHq9jdwUiNkopde+996qkpCS1ceNGdejQIbVixQoVFxenKisre7R+lypQ8Tlff70vKxWY+Pjr3iyJTz9wxx13qKioKGWxWFR6erp67bXXfPZv3rxZzZw5U4WHh6vg4GCVmpqqHnzwQZ/M+rPPPuvwW3x//QULRGxefvnldvuv+5tAfXYqKirU0qVL1aBBg5TdblfLly9v1cLRH1wsPo888kibn4Nhw4Z5j2krPjt37lRXX321ioqKUmFhYWrGjBnqww8/7KFa+UegYuN0OtV9992n4uLiVFhYmMrIyFD79+/voVr5T6Dic77+el9WKjDx8de9Wcb4CCGEEGLA6BujNYUQQggheoAkPkIIIYQYMCTxEUIIIcSAIYmPEEIIIQYMSXyEEEIIMWBI4iOEEEKIAUMSHyGEEEIMGJL4CCGEEGLAkMRHCCGEEAOGJD5CCCGEGDAk8RFCCCHEgCGJjxBCCCEGjP8Ch4mMdCFzdbcAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "580870.849586115 1.1181742759545388\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "597153.8167352047 1.1410015561011082\n"
     ]
    }
   ],
   "source": [
    "for t in receivingList:\n",
    "    plotPoly(hdCP[t].buffer(0.1))\n",
    "    for u in HDunitList[t]:\n",
    "        plotPoly(unitGeom[u], 0.2)\n",
    "    for uu in linkerLists[receivingList.index(t)]:\n",
    "        plotPoly(unitGeom[uu])\n",
    "    plt.show()\n",
    "    print(HDvPop[t], (HDvPop[t]+unitPop[CCBu])/aDP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 151,
   "id": "7cb2cf34-28dc-4380-8216-b28371b751a2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "now, for CCB unit 2727 tack on this CCBu where it won't overshoot pop too much and won't create enclaves or district discontiguity\n",
      "After CCBu tack-on, its use is now 0.88453\n"
     ]
    }
   ],
   "source": [
    "print(\"now, for CCB unit\",CCBu,\"tack on this CCBu where it won't overshoot pop too much and won't create enclaves or district discontiguity\")\n",
    "for i,t in enumerate(receivingList): \n",
    "    #unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t]+[CCBu],unitNbrs)\n",
    "    #if unbroken and noEnclave:\n",
    "    HDunitList[t].append(CCBu)\n",
    "    HDvPop[t] += unitPop[CCBu]\n",
    "    for u in [CCBu] + linkerLists[i] :\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "print(\"After CCBu tack-on, its use is now\",r5(unitUse[CCBu]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "id": "405e1bd6-0051-4a34-ac6c-558b82c03a60",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(check again -- any more disco's ?\n",
      "working on HD 0 time is now 0 sec\n",
      "working on HD 513 time is now 3 sec\n",
      "working on HD 1015 time is now 6 sec\n",
      "working on HD 1520 time is now 9 sec\n",
      "working on HD 2028 time is now 12 sec\n",
      "working on HD 2530 time is now 15 sec\n",
      "working on HD 3032 time is now 18 sec\n",
      "working on HD 3535 time is now 20 sec\n",
      "working on HD 4038 time is now 22 sec\n",
      "out of 4070 total HDs, there were 4070 0 0 0 HDs that were clean, discontig only, enclave-only, both problems after triage\n",
      "this took 23 seconds with maxLoop =  5\n"
     ]
    }
   ],
   "source": [
    "print(\"(check again -- any more disco's ?\")\n",
    "maxLOOP = 5  #can increase to avoid false enclave detection\n",
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()\n",
    "startTime = time.time()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%500 == 0:\n",
    "        print(\"working on HD\",t,\"time is now\",int(time.time() - startTime),\"sec\")\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs, maxLOOP)\n",
    "    if not noEnclave:\n",
    "        noEnclave, enclaveList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems after triage\")\n",
    "print(\"this took\",int(time.time() - startTime),\"seconds with maxLoop = \", maxLOOP)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6150cac-2249-415b-a364-edf55dc441ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "114705bb-9640-45f1-9f25-030030efaa63",
   "metadata": {},
   "outputs": [],
   "source": [
    "#below here -- working on tightening use distro while squaring up pop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 153,
   "id": "5d7d8519-eb3d-4345-9ac6-ab888e61c348",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pre-patch avg use and its sd are 0.9625 0.12599\n"
     ]
    }
   ],
   "source": [
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        latestHDpop[t] += unitPop[u]\n",
    "        latestUnitUse[u] += nDistricts * HDweight[t]\n",
    "latestUnitWeights, latestUnitDistro = list(), list()\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "id": "b1971853-bda7-49a4-9f25-1bdfd5e75aa2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on avg unit-to-HDcp dist for HD 0\n",
      "working on avg unit-to-HDcp dist for HD 801\n",
      "working on avg unit-to-HDcp dist for HD 1601\n",
      "working on avg unit-to-HDcp dist for HD 2403\n",
      "working on avg unit-to-HDcp dist for HD 3203\n",
      "working on avg unit-to-HDcp dist for HD 4004\n"
     ]
    }
   ],
   "source": [
    "avgDist = [0. for t in range(nHDs)]  #about 6sec per 1000 HDs\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%800 == 0:\n",
    "        print(\"working on avg unit-to-HDcp dist for HD\",t)\n",
    "    avgDist[t] =  np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 214,
   "id": "f5b99900-614a-47df-b7de-5d59fffd6d3a",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before patching, make another copy of the current HD lists\n"
     ]
    },
    {
     "ename": "NameError",
     "evalue": "name 'latestUnitDistro' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[214], line 20\u001b[0m\n\u001b[0;32m     18\u001b[0m         latestUnitDistro\u001b[38;5;241m.\u001b[39mappend(latestUnitUse[u])\n\u001b[0;32m     19\u001b[0m         latestUnitWeights\u001b[38;5;241m.\u001b[39mappend(unitPop[u]\u001b[38;5;241m/\u001b[39mstatePop)\n\u001b[1;32m---> 20\u001b[0m plt\u001b[38;5;241m.\u001b[39mhist(\u001b[43mlatestUnitDistro\u001b[49m, weights\u001b[38;5;241m=\u001b[39mlatestUnitWeights, bins \u001b[38;5;241m=\u001b[39m \u001b[38;5;241m20\u001b[39m, histtype \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstep\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m     21\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n\u001b[0;32m     22\u001b[0m latestAvg, latestSD \u001b[38;5;241m=\u001b[39m getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
      "\u001b[1;31mNameError\u001b[0m: name 'latestUnitDistro' is not defined"
     ]
    }
   ],
   "source": [
    "#Restart - may want to comment out first line\n",
    "HDunitList = [latestHDlist[t].copy() for t in range(nHDs)]\n",
    "unitUse = [0. for u in range(nUnits) ]\n",
    "HDvPop = [np.sum([unitPop[u] for u in HDunitList[t] ]) for t in range(nHDs) ]\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, weights = unitPop,bins = 50)\n",
    "plt.show()\n",
    "plt.hist([HDvPop[t] for t in popHDlist], bins=50)\n",
    "plt.show()\n",
    "print(\"before patching, make another copy of the current HD lists\")\n",
    "latestHDlist = [HDunitList[t].copy() for t in range(nHDs)]   #More safekeeping\n",
    "latestHDpop, latestUnitUse = [0. for t in range(nHDs)], [0. for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if latestUnitUse[u] > 0.1:\n",
    "        latestUnitDistro.append(latestUnitUse[u])\n",
    "        latestUnitWeights.append(unitPop[u]/statePop)\n",
    "plt.hist(latestUnitDistro, weights=latestUnitWeights, bins = 20, histtype = \"step\")\n",
    "plt.show()\n",
    "latestAvg, latestSD = getWeightedAvgAndSD(latestUnitDistro, latestUnitWeights)\n",
    "print(\"pre-patch avg use and its sd are\",r5(latestAvg),r5(latestSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "id": "fa933848-9596-4201-8e7b-5dfbf4453ea8",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"ContigButOffPopUnit.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 215,
   "id": "27b51cd0-8bb6-4b16-bb79-37498e59ce5c",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We will now square up the 558 HDs with pop < 706178 to within 1249\n",
      "working on squaring up HD 41 time is now 0\n",
      "working on squaring up HD 604 time is now 143\n",
      "working on squaring up HD 1179 time is now 886\n",
      "working on squaring up HD 1737 time is now 2032\n",
      "working on squaring up HD 2409 time is now 2887\n",
      "working on squaring up HD 3774 time is now 3146\n",
      "We have addressed underpop in a total of 558 HDs\n",
      "Here is a scatterplot of original (x) to final pop (y)\n"
     ]
    },
    {
     "data": {
      "image/png": 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twaE1Slx5fDsJIzVxZZ3/ir1fIWP1AQcXMGv7DJb3K+feUyIePf05JCFEEITPQX3V9IE18FiI6oZWPPVRMaa/U9Thge1OpOJc7OG3Tbu3B/acuaK7YBODdf5Ax3g4PZrW8n3mLPVN6BIayLSPpz+HlD4vAaXPE4R3Qn3V9EGr/lmeaMEhV0coJjwIHODQMsRIGYesPbyE7nWxbMqc7BTERASrLjWhpK+Y/Xnd8TmkXmMaQUKIILwX6qvmfpTWEOoc0gk/Nt8U3OYJcSpWWfrCtQasLTgvOEfAOPdOm5XD+0cqsGLvV7Jjnev1ONcpqmloxoq9X6kuNcFSm8kZd9aTUvL8JtcYQRA+CXN2C6EaVpdG14hgPJXZV1QEAZ5JqbePcxmVHIdRfeLw80GJ2H78O9E5AsbJOAwMMCGuC1uaunMcjv17r7vRgnlbT6kuNcHiIjU5adsEA30OKWuMIAifhfqquRe5AntAe1B04eLx+DtjDJCnA2e9LePQ1Xg4LVphsNRm4jggJ3sA4rqEGO5zSBYhgiB8GleK1xHSyAXfmgD86cGBCO4U4DUB7N6WcehqJpirRRYB9rWI6xJiyM8hCSGCIAhCNawuSC1Tt92JUQQbn321q/iyZMaaq5lgWgg/o6yZWsg1RhAEQQBQ36CWxQXJ2n3d05YCJf203IXSHnm8GJXrWC+EFiLGCGvmCpQ1JgFljREE4S/o1aBWzXmUCDS1Ys55jp7KOHSlO7ya965VqQmjZWlS+rxGkBAiCEIrtHhAuwtXHr5qULIWSoSTlmJOL2FoDy9KxGJ23FViYN+ZK3hy6ynB8wHs198TayYGCSGNICFEEIQWGOkB4SxChvWMwZiXD6p6+Lpb3CkRaO4Qc3qLV9YClc41gVxBqgiimnvUKIJfyfObYoQIgiDciNgDmq/R4ulqyrERQahuaBXdRyxd3N3ijjWtu0tIEL7/sRkr9nwpOfYPfyvBjZY2mKPCmB/OfMahXuidsSZXBDEnW/m11HvNtICEEEEwYpRfOoT3oEWNFq0Qe+hJiSB77B++eog71rTuRzcdlT0WB6CqoQVPfXwagLFaZdijZ/aVXBFEE4AVe0sxMbXjvelr34UkhAiCASO5NgjvwSjF+VxpjsrDP3z1EnfurNPjCWscC3pmX6m9N33xu5DqCBGEDPyvX7Xl5wn/xSjF+Vgq/4rhXN9HiwJ8LLiz5ozRWmXw6NEdnkfNvanldyFrnSQ9ICFEEBLI/foFjPdlShgHoxSaUyu0hB6+eok73jriLjzR24wFvXrkKb03tfwuzCupRMbqA5j+ThEWbC/G9HeKkLH6gMd+VJJrjCAkMIprg/BOjFJojvWhFxsRjOqGFtv/+YJ8E1LMKCyvwvfXm3DterOm5xQjMMCEnOwUPLn1pEvHkcPTrTKE4m306JGn9N7U6rvQSMkDPCSECEICo7g2CO/EKNWUWR96/3p2LE5crHF4+OaXWjrUtgkwAWI//LUUdzERwS4fQw5Ptn2Qi7dx548rlntz2r09sOfMFXTrEgpLvevfhUZKHrCHXGMEIYFRXBuE96KXq0MK1tiT4E4BDg1q80stgjEhUiKIP5aecSzOc+gaEYxXH7obsRFBkuM82dvMCLGHYvdmdHgQosKDsLbgG5vrasWeL5mOKfVdqFd8mVLIIkQQEhjFtUF4N3q4OljmoKQfFUummbNliKW3lRKU/sDgV/OPD6YiKzUBESGBkm0fPNXbzFXLiJbp68735oVrDVhbcL7DOLkyCyzfhUa1sJMQIggJjOLaILwfIxSaUyLIWDLNrByQkz0AcV1CPBLH4oyzEHOlGak7cSXeRkn6Oqtg4u9NvsWHHGq/C41qYSchRBAyGPXLlCDUwCrIWH+Vx3UJwZTBt7s6LUHkfohwAJ7KTEavuAjRB70RrHHOsK5tfqmlQw0f1kBjNfV+WMssxIgE1ct9FxrVwk5CiCAYMOKXKXELX6t0awSM8utdix8iRrDG2cO6Zu8duWDLIlPiTuNju5RmZrEKtJzsATBHhSn+vBnVwk5CiCAYMdqXKdGOL1a6NQJG+vXuaz9E+LWVs77YixtWd1pReZXq+CNWgWaOClP9XWhECzsJIYIgvBYj1iTxFYz2692Xfojwazt3i3SNJPtYIVZrTeG311THH+klfnlhW/RtFQrLqwBwSL8zDmkeur6UPk8QhFdCVb/djxFS/32VrNQEzBrVi2ksbwVjg02YCgkrPVt85Jda8Psdp7H+YBnWHyzHo5uOeqy6NAkhgiC8EqPWJPE1slITcHjROHz4uxGYP7YP5o/tjVd+eTcmpJg9PTWvJ5NxDXlXYEJUqKjM4esisVrNxISVHuJXrIZSpYf6N5JrjCAIr8SoNUl8kfxSi0NMx/qD5T4fh6VHAL5SV9S0e7sL1vixt9ak3dnVZfeWKzFZcusmV5+Kg/7VpUkIEQThlRglq8nX8cc4rH1nKrF0V4lDirg7hB9rHJazEHXGOdBYi9guNTFZLIkLLCn6evdvJNcYQRBeCaurwN1ZTW1WDoXlVdhVfBmF5VU+FZPkj3FYK/eV4smtJx1EEOA+t42cKwqAoBuJ56nMvji8aJyDQPNEbBdryxBL3Q2m47GO0wKyCBEE4ZUYIavJF1L3pVwZWnUc9xb2nbmCtw9ViG53l9tGzBUFABmrD4i6kUwAth+/hPnj+nTYNiHFjC6hQR2ystzxeVBS4+hIWRXTMZ2FqDshIUQQhNfiyZokvuAykhNy/hSH1WblsHRXiey4yromFH1bhQCTSdP4ISFX1JEydanwQtf1k5OX3faZYK5x9G0V8r+6ynTM2M4hGs1OHhJCBEF4NZ4otudq00wjwCLk/CkO61hFtWxjUZ55H55E7Y1bY91hBcwrqcTzn5xlGmsvRD0h0JlrHJVXoe4G2xp301EIUYwQQRBeD/9resrg25HuJvO/Pd6eus8a+zOsZ4wh4rD0QIlVq9bpYe4cB+MqvJhxPo8YvBDVO6aLj487f/U64x4Kzqvj7wcSQgRBEArxdpcRq5A7cbFGtwJ7nsYVq5aWIkMuvdweZyGqh0Dnxc+KT7/EvX/Mx/R3irD+YDnTPNPvjGM+z7Ufm1XPUSkkhAiCIBTi7S4jJULOX6pL81mIatHKCsjaAZ7HXoiyXtcjZddUCba8kkpkrD6A6e8UYdORC0yuRIcaR727IjYiiOlcen52KEaIIAhCIVr2ZNKjcJ8zSoWcrzU9FcI+C9EVm46rVkDW/aPDg7DqFwMdhCjrdV1/sAyfnPy3orgmsdgjOZwTF16akoont56S3EdvdysJIYIgCIVolbrvqfR7NULOl5qeiiGWhRgbEYRfp/XCuv0dqzo746olg3X/N6cPxahkR1eT3HW1R0nwtBJ3Hc/8sX0wqk9cB8H8wKBEPP7vWtEyBSbo724l1xhBEIQKXHUZsRagcwd6Ntf0Nvjeattmp2HdtMHYNjsNx/8wAf89PlmXwHE5Fx1/HqFO7VLX1RklcU1K3XUAkBzfWTRxYfEDKfjzI0MRGxHs8HqCh9ytZBHyAJ4whRMEoT1qXUZGSL/3ZA0moyNm/XJ3AU/+2ZCS0EVSeEidR+y6CsFaEFONu+/a9Wa0WTnReT4wKAETU43hbiUhpDO+UImWIIhbqHEZGaVisz/E/miJO8Wj0LNBiDmjk2TPw1/XtfnnZDO6AHmho8bdt2LvV3j3cIXkuhjF3arINdarVy+YTKYOf/PmzQMAbNy4Effffz8iIyNhMplQW1sreqzm5mYMHjwYJpMJxcXFDtvOnDmD++67D6GhoejevTvWrFnTYf8dO3agf//+CA0NxcCBA7Fv3z6H7RzH4YUXXkBCQgLCwsKQmZmJ8+fl/bvuxJOmcIIgjIOR0u/1rsGkJZ7o8ybkOnPu9aUUsWeDMyYAu09XMr3PwAATRvW5jen8ckJHrq+fGN7ybFMkhI4fP47KykrbX35+PgDgoYceAgA0NjYiKysLS5YskT3Wc889h8TExA6v19fX42c/+xl69uyJEydO4OWXX8ayZcuwceNG25jPP/8c06dPx6xZs3Dq1ClMnToVU6dORUnJrfLoa9asweuvv44NGzbg6NGjiIiIwMSJE9HU5Jm6Hv7YvJAgCGG8Pf3eCNinci/YXozp7xQhY/UBXR66WopHJYHISlP0tWpMrCT2yB5vebYpEkK33XYbzGaz7W/Pnj3o3bs3xowZAwBYuHAhnn/+eaSlpUke5+9//zv++c9/4pVXXumw7cMPP0RLSwvee+893HXXXZg2bRr++7//G//f//f/2casW7cOWVlZePbZZzFgwACsWLECQ4cOxfr16wG0W4Nee+01LF26FFOmTMGgQYPwl7/8BVeuXEFubq6St6wZ3l6JliAI7dDqAeWv+JJ1XU0gMqulUMugeLHkgMhQ6Qgb/tn2/pEKw4oh1VljLS0t2LJlC2bOnAmTiV0jXr16FbNnz8Zf//pXhIeHd9heWFiI0aNHIzj4VjT5xIkTce7cOdTU1NjGZGZmOuw3ceJEFBYWAgAqKipgsVgcxkRFRWHEiBG2MUI0Nzejvr7e4U8rjGQKJwjCs1DWlnp8zbqu5jtfiaVwQooZCzOTERXmWMhQTUFMIbfg8sl3Me27Yu9XulnslKJaCOXm5qK2thYzZsxg3ofjOMyYMQNz587FPffcIzjGYrEgPj7e4TX+/xaLRXKM/Xb7/YTGCLFy5UpERUXZ/rp378783uQgUzhBEPb4S8VmrfE167qS73yllkLefbi24Lytb1l0WBCeyuyrOq7J2S1ojgpj3teoFjvVWWObNm3CpEmTBON8xHjjjTdw/fp1LF68WO1p3crixYvx9NNP2/5fX1+vmRjSshItQRC+AWVtKcfXrOusRRCVWgrFKkHX3WjFawXfoJ+5syZiW0kRR71KQyhFlUXo4sWLKCgowO9+9ztF+x04cACFhYUICQlBp06d0KdPHwDAPffcg8ceewwAYDabcfXqVYf9+P+bzWbJMfbb7fcTGiNESEgIIiMjHf60gkzhBEEI4c1ZW57A16zrrIHISiyFeroPlQZSG9Fip0oIbd68Gd26dUN2drai/V5//XWcPn0axcXFKC4utqW8f/TRR/jjH/8IAEhPT8ehQ4fQ2nqrmVt+fj769euHmJgY25j9+/c7HDs/Px/p6ekAgKSkJJjNZocx9fX1OHr0qG2MJyBTOEEQhGv4YqC52LMhNiIIs0b1kk3Rdy4jUFRepav7UGz+UhjJYqfYNWa1WrF582Y89thj6NTJcXeLxQKLxYKysjIAwNmzZ9GlSxf06NEDsbGx6NGjh8P4zp07AwB69+6NO+64AwDwyCOPYPny5Zg1axYWLVqEkpISrFu3DmvXrrXtt2DBAowZMwavvvoqsrOzsX37dnzxxRe2FHuTyYSFCxfipZdeQnJyMpKSkpCTk4PExERMnTpV6VvWFDKFEwRBqEerPm9Gg+XZINSVIL/U0qEQY3QYW4d3LcUIP//3j1Rgxd6vZMcbyWKnWAgVFBTg0qVLmDlzZodtGzZswPLly23/Hz16NIB2CxJrUHVUVBT++c9/Yt68eRg2bBji4uLwwgsvYM6cObYxI0eOxNatW7F06VIsWbIEycnJyM3NRWpqqm3Mc889h4aGBsyZMwe1tbXIyMhAXl4eQkM9v/hGqaZJEAThjfhqexCpZ4NQ5eno8CDUNrZ2GMsHRssh1wZDKYEBJswYlYR3D1d4VTysieM478gx9AD19fWIiopCXV2dpvFCBEEQhOu42rfRHX0f3XFMscBnLXBHiyd+voCwxU6PUBAlz28SQhKQECIIgvBN3NH30R3HbLNyyFh9QHHRRVbcJU483VeThJBGkBAiCILwPcQsLK6IAnccEwAKy6sw/Z0ixfspgXdXHV40TtPYKndYx1hR8vxWXVCRIAiCILwNd6SWuzNdXY/sKneltHtLaQjVBRUJgiAIQi2eshYoqUzNmtTijmPy6JldpVdKO3/tLfVNqP6xGbERwTBHhXksg5qEEEEQBKErnowfcUdlandWu+brJrkrRsgePUSX0LXn0TOGyB5yjREE4YBzcTZvaV5JeAee7hzvjsrU7qx2HRhgQk72AMX7KUGvIpRi156n0kO9yMgiRBCEDU9nehC+jVwsjR59qNzR99HdvSRjIkIUjY8O6wSTyYQagRpDQnMD3F+EUura28NB/15kZBEiCAKAfr/UyeLkvxihc7w7+j66u5ekUpda7Y2bTCII0K/Fk9y1t0fvXmRkESIIQrdf6mRx8m+M0jneHZWp3Vnt2h2xO9FhQXjz0aFIu1OfbC6l11TPXmQkhAiCcGvWC49YnRXe4kSNh30fo3SOb7NyiAoLxnMT+6G6oQWxnUNgjnQ9c82+X5h9RlRUWLBLrSzkXG9qqL3RigCTSTf3k9Jrqme2HAkhgiDc/kvdCLEhRkPP9HFPFrazx92xNCxIWSW1WJPAABPqbrRgTd7Xmlk+7RvNaomeVhclYk6PwG17KEaIIAi3/1I3QmyIkcgrqUTG6gOY/k4RFmwvxvR3ipCx+oBbsmX0PJccLLE00+7tgT1nrrglfkyPODh3nYN3vSVEaWcp0dPqYn/tpTDB/YHbzpAQIgjC9mtN7KvH1fRao8SGGAE908c9naouBP9Aj490fAhHhwchKjwIawu+cUmwiQXju7P6s/253XmOrNQEHF40Dttmp+G3o3rBpFIrqP08syY6iI2TE3MJOgVuO0OuMYIgHEzvJgh3jHblV5pRYkM8jZ4uQuO7Ix1nJpTlpDR+TMrtFRUW7PY4OD1i7fi2FQCw+cgFVccA2D7P9i7VC9casO3YJVjqm23bnd19bVYO6w+UYfORCtTeuHU9YyOC8dKUVDwwKEE0jooqSxME4XHcmfVihNgQI1BUXuX2ByWPHg9lNYgFzQuhRLDJBeP/dlQvpvm5YpXU0vIpF9eldp6ssUpSFaB57IUqADy/8yxqBQRtdUMLntx6Eo//OwmLH0hxEHNGgIQQQRA27H+taRlY626LkzeQV1KJ5z85yzRWCxehEd2RrEX17GERbCzWr13FV5jO54pVUivLJ0uZiTgFRRa7RgRjyuBETEgxM32eWcUqv7aLd55lqlv09qEK3H1HNB4YlMg8dz0gIUQQhAPu+rXmTouT0VFiBQG0cREa0R2ppKieM1KCjcX6VdXQgtiIINQ0tLrNKqmF5VPOsvXmI0MQExGCz8uvMc3pDw8MwMyMJOYfGUrFKgdht6YYS3eVYGJqgqF+9JAQIghCN9xlcTIySh4sWroIhyfFIjo8SNBVwRMTHqSrO9IV65OUYGM97oODb8d7Ry64zSrpquWTJdh6/rZTUBJr3S0yRNF7ckWsslDd0Kq7O1YOyhojCEJXeIvTlMG3I723PlVtPYnSB4ueLkK9m5uosT6xZDixHjczxYy3fjUUZqesJS3bTPCWTzXnYLlXlCacKV1zPVylRssOJYsQQRCEG2H90o8OC8Kq/xyomYvwWEW1pDUIAGob9f11rrRCMqulRolLKjDA5HarpFrLp5YCQYl10T4w+/+++UGzOYhhtOxQEkIEQRBuhPVL/81Hh2JUnzjNzmvEYGkp15EQrPFjSl1SemQtqTmHVgJBiatv35krWLqrBNUN7HE+zueJCg9CXaNw7JUzeleNZoGEEEEQhBthtVak3antg9lTwdJyad9iQfMJUaHIyR6AmIgQVZYaXwjGH54UC3NkiEOtHjXERgTjjw+myr7nlftK8fahCtXn4dcWALO4nXZvd+w5c8VQ8YEkhAiCINyIp0oHeKJ2E0vaN+C+oHlvD8bPL7Wg6abV5eNMvjtBVgTtO1OpWgT9Jr0nJqUmOKytkAi1JzqsE2AyYW3BedtrrvRf0xITx3F6x8t5DfX19YiKikJdXR0iIyM9PR2CILwYVpGg9Tn5Rp1CAkzLdgZiad/uOJcvorTEghRdI4Jx7A+Zktlp9/6xANUNLaqOv212mqDbj7cG5pdakFt8Rfb47rw3lDy/ySJEEAShA56wVujlLjJ+Ow9jw1JiwWQCWM0WVQ0tkkHwxyqqVYkgE4D4yBBYOQ67ii93uIcDA0you9GCzUcuaF453J2QECIIgtAJT7QW0EOAGbWdh7fAkjbPi6DgTgFoYXCfSQXBqw2Q5wA03bTi0XeP2l6zt2q6q3K4uyEhRBAE4eO4W4AZMUPNm1CyLp1DOqH6prw1RyoI/sK1RubzOeNcksG+35hcY1spPHlvUEFFgiAIwiWM2M7Dm1CyLtU/tQoRs+fJFaBss3LYduyS8kmKwFt/ln9aCkvdDdXH8eS9QUKIIAjCD2izcigsr8Ku4ssoLK9Cm9ISxRLwGWpqH87+Dr9+rDw4+HYA6LDeLFmIxyqqYanX1vrCu7fUxh15+t4g1xhBEISP4+6MNZYSATnZKboEisvVMTIi/PrN/SnDT47MFDPuTYpVFQTvThdUbOcQRXWQ3Fk+QgkkhAiCIHwYuW7mWvfYEno4T747ASv2ur90gCdKFGhFVmoC/vzIEMmmqlq0CnGnC+pSVaOiOkhR4UFY9Qvt2sqoheoISUB1hAiC8GbarBwyVh8QDWDlH6yHF43T7Be5s0WmpqEZ87aecnt9IV+pY7TvTCWe3NrRMqTV+2izchj2Ur5sHzolmKCszYb9fu66Lkqe3xQjRBAE4aMoSWvXCj5Dbcrg2zE8KRYr9n4lWl8IaA+ydTVeSa6OkVbn0YMHBiVgw6+GdogZYuleryWsstjeFapmdY1wXcg1RhAE4aN4Oq1dr/pCrOcpKq/CqGTtGtu6C5baT1KxUFLbjlVUM1mDYiKCHYKfE35yce4+XdnB9Tnt3u4OrTNY4a/L+0cqMGNUEhVUJAiCILTF02ntegmx/FIL07h5W09i1X96PiaFBanaT1KxUAA6bIsOC8JvRyVh/rg+zGudkz0A5qiwDmLquawBHUTWnjNXXHinwIq9X+HdwxUei+UiIUQQBOGjeKLxqj16CLE2K4fcYrYHce2NVk0DxF1BbXabVPC7WNZZ7Y1WrC34Bps/r8BvR/Zimp85KkxQiAkJNC2EtNbB+0qgGCGCIAgfhU/LBtTVnHEVPeoLqemb5em4lLySSmSsPoDp7xRhwfZiTH+nCBmrDyCvpFJyP5ZYKClqG1uxtuA8osPVF2QUQu46s+DJWC4SQgRBED4Mn9Zu9kDwrR5CTKlbzR0B4krgLTrOMU28RURKDLH0JFOCVtdE6jorwVPXhlxjBEEQPo4ejVelzi1WX4glJkTOhaTWLaNlgDirm0vOouPcid35uFpVhK5tbMVTmX2x/fglVddECLHrbDLdahjLit59x0gIEQRB+AHubrwqxYQUM7qEBqGwvAoAh/Q745DWu6usEGMpkCgXByWGVgHiSoo4Ksmiq7vR0uG4sRFBmswZAHrFhePwonGqMs/EsBfcBaUWbDpyQbEIAvTvO0ZCiCA8hDe2AiAIpQgJhU9OXpa1PLBWxJZq7yGElgHiSqt2s1o6CkoteO/IhQ7HrW7QrgjitevN2HPmCrp1CcXPByU6fPe4UqE7MMCE4UmxeOqjYsVzcnfwvuh5qbK0OFRZmnAX3twKgCBYRbzaas9qKmILfaaE9pM6rxLUzLGwvArT3ymSPXZsRJCs6BHq6cb6MA8wwaGNh/13jxYVulnfp9rjs6Dk+U0WIYLQGb16PxGEO2AV8UrjYexRU4jROQ7qwrVGbDt2ySGuxpUYGGfUzJF348kFPLNYfpwLHprt6gg9v/OsZNFE56Qs/rvnzUeGSFYCl7pm9qiJ8dHy2iiFhBBB6IgrDweC8DRKRLwrVaXVFmJ0joOaP66P29zPauYYGGBCTnaKYC8xpYgVPATaY7LWHziPzUcuoPbGLUHkbAni4b97lu4qkRRhrJXAlcT4TEo14zfpvTwaGkBCiGCGYlpcR6+WAwShNUpFvCtVpbUqxOjOAHG1c4yJCNbk/GIFD4H2970gsy/mj0u2fWdfu96MFXu/Ej0eB/YYJLlrOzwpFuZItiy34u9qsf4Rzz5LSAgRTFBMizZ4uvcTQahFqYh3Rcx4uiI2C2rn6OpnW8l7txeCfzv5b5fOaw+LAF02OUW00rU9RvjhRwUVCVlcKQDmy7RZORSWV2FX8WUUllcxVUP1dO8nglCLUhHvSlVprQsxqvmsyqF2jq58ttUWPMwrqZS0BtkTGxGsSdXpCSlmTEo1M53zSNk1j1b6JosQIQnFtAij1kLmDb90CUIIpSJeKq2d5YHuaiFGHndasyekmLEwsy82H6lwiMWRmqPaukdyxxVDLK7LGf67Jyc7BfO2qrtm9ueUy+CzZ/3BMnxy8t8e8zBQ+rwElD7Pnga5bXaa38S0uJpeyu8PCH/RUNYYYUT4dHE5EW+fLg64LkRciU3UIhVcbC4XrjX8lJXWbNve3uW9F+aPS5acI6s44Zk/tjdG9blNcVymXIq/Mxt+Wg9XrpnS98ZD6fOEYaGYFke0sJBp9UuXIPRErYXH1fYeagOetbZms1g56m604rWC8+hn7iL5Oea/A5bt/tJBSDnDi8unJvRTZXFX25tM7TWTWnM5POlhICFESEIxLY5olfXlyd5PBKEWtSLeE+09tMzQZLVyKHmY898B6w+UYW3BNx22a9GUVskPVOd5q7lmrjaF9VTWLAkhQhKKaXFESwuZJ3s/EYRavEXEa/VZVWrlUPIwb09zT0Y/c+cO4jImIggPDr4dUWHBaLNyqtZXyQ9UsXnLuSbtt5+/+qPiOQpBTVcJQ+FqwKOvQRYygvAOEa/VZ1WtlUPJw9xeXOaXWpBbfAXVDS3YdOQCNh25oDq4W01gtv285WKFlAZFs6L39yelzxOy8OZwc5TjzWmOCvW7wF5XUoIJgtCP4UmxiA4X79bO+llVa51Q+jAPDDCh7kYLNh+54NA6AxAvVeJcFqDlptXh/wBsKf5K5y1XNmXlvlLB7XIEmDqWG+Dx1PcnWYQIJrzFHO5uyEJGEN5BfqlFst8WB7bPqlJBozZcQGlwt5A1RqyZantgdqlkpWf7ebPM5Z3/q1AUFM2v8uz7krDxUIWhvj9JCBHMeIM5XA8o64sgjA3/IJciJjwIE1LkC/4pdS+xCixnlAR3191oEQzeFmumOmd0EqR60zuLkMLyKtm5KC28Y//9ePcdMT/1NevYNNYT35+KXGO9evWCyWTq8Ddv3jwAwMaNG3H//fcjMjISJpMJtbW1HY4xefJk9OjRA6GhoUhISMCvf/1rXLlyxbb9woULgucoKnKsZbNjxw70798foaGhGDhwIPbt2+ewneM4vPDCC0hISEBYWBgyMzNx/vx5JW+XIETJSk3A4UXjsG12GtZNG4xts9NweNE4EkEEYQBY4npqGltxrKJa9lhSFaTFOHWphnHkLVhdcJb6Jubgbe6nv7cPVUim6TuHOWgVrDx/bO8O34/tVa5LHURQbEQQcrIHeOz7U5EQOn78OCorK21/+fn5AICHHnoIANDY2IisrCwsWbJE9Bhjx47Fxx9/jHPnzuGTTz5BeXk5fvnLX3YYV1BQ4HCuYcOG2bZ9/vnnmD59OmbNmoVTp05h6tSpmDp1KkpKSmxj1qxZg9dffx0bNmzA0aNHERERgYkTJ6KpyT/q3RDuh7eQTRl8O9J7dyV3GEEYBK3rn4nFSYrx9qEK7DtzRX6gHawuuOofmzUNTu4aEYx/PTvWQYRoFaw8qs9tDt+PYnFHNQ2tmLf1lMfaNSkSQrfddhvMZrPtb8+ePejduzfGjBkDAFi4cCGef/55pKWliR7jqaeeQlpaGnr27ImRI0fi+eefR1FREVpbHX25Xbt2dThXUNCtoLd169YhKysLzz77LAYMGIAVK1Zg6NChWL9+PYB2a9Brr72GpUuXYsqUKRg0aBD+8pe/4MqVK8jNzVXylgmCIAgvwx3ZnVmpCfjXs2Px67QeTOOX7ipR1D9rWM8YyP2WCjAB0eHadK/nqWpowYmLjhYslqQQqbkKBT3LxR0B7TFQnug5pjprrKWlBVu2bMHMmTNhMqn7JVxdXY0PP/wQI0eOdBA6QLsLrVu3bsjIyMDu3bsdthUWFiIzM9PhtYkTJ6KwsBAAUFFRAYvF4jAmKioKI0aMsI0Rorm5GfX19Q5/BEEQhHfhjuzOvJJKjHn5IP5adIlpfHUDm+uN58TFmg4xPs5YOaC2sUV6kAqcLWMsDWVn35cEk8R25zgpJTFQeqNaCOXm5qK2thYzZsxQvO+iRYsQERGBrl274tKlS9i1a5dtW+fOnfHqq69ix44d2Lt3LzIyMjB16lQHMWSxWBAfH+9wzPj4eFgsFtt2/jWxMUKsXLkSUVFRtr/u3bsrfm8EQRCEZ9G6e72YS0cOJbE2rGNjI4IlRZ4ahCxjcmVTFj+QwlxWpc3K4UjZD0xz8US7JtVZY5s2bcKkSZOQmJioeN9nn30Ws2bNwsWLF7F8+XL85je/wZ49e2AymRAXF4enn37aNvbee+/FlStX8PLLL2Py5Mlqp8vE4sWLHc5dX19PYojwSVxpZOlP0Dp5L1pld7rSP0uJ6411rDkqTLSEhzNy2wFpy5hQ2ZRhPWNw4mINdhVfRrcuofjXs2Nx4mKN6GdEadFFTxSjVSWELl68iIKCAuzcuVPVSePi4hAXF4e+fftiwIAB6N69O4qKipCeni44fsSIEbbAbAAwm824evWqw5irV6/CbDbbtvOvJSQkOIwZPHiw6LxCQkIQEhKi6j0RhLfgajdwf4HWyXNoJUC1qH+mtrK0UtebknZGgQEmQZHnXEfIHBWKyXcnYOMh8Zo/k+9OkFwP+7IpvHtQ6DMxZfDtHfZV0onek+2aVAmhzZs3o1u3bsjOznZ5AlarFUB7fI4YxcXFDoImPT0d+/fvx8KFC22v5efn24RUUlISzGYz9u/fbxM+9fX1OHr0KJ544gmX50wQ3orYFxNfb8TfKoWLQevkObQWoK7WP1PjqjFBeS0hpcVapaw1QqLv7UMVgufdeKgCQ3rE2NZWTIQq/UwosaR5uhitYiFktVqxefNmPPbYY+jUyXF3i8UCi8WCsrIyAMDZs2fRpUsX9OjRA7GxsTh69CiOHz+OjIwMxMTEoLy8HDk5Oejdu7dNxHzwwQcIDg7GkCFDAAA7d+7Ee++9h3fffdd2ngULFmDMmDF49dVXkZ2dje3bt+OLL77Axo0bAQAmkwkLFy7ESy+9hOTkZCQlJSEnJweJiYmYOnWqqoUiCG9HaeVaf4XWyXMYUYAqddV0DumEVx4apGqeSt15QiLP+f9tVg67T0unpfP3c36pRVCE5mSnYMVeZZ8JJZY0TxejVSyECgoKcOnSJcycObPDtg0bNmD58uW2/48ePRpAuwVpxowZCA8Px86dO/Hiiy+ioaEBCQkJyMrKwtKlSx1cUitWrMDFixfRqVMn9O/fHx999JFDraGRI0di69atWLp0KZYsWYLk5GTk5uYiNTXVNua5555DQ0MD5syZg9raWmRkZCAvLw+hodQMk/BPlGRt+HMFcVonz2BUAaq0snSX0E5MFavF0LqdEev9vP5AGV4r+EZQhD659aTkOYQ+E0osaTnZnnU3mzhOaaFs/6G+vh5RUVGoq6tDZGSkp6dDEC6xq/gyFmwvlh23btpgQX+/v0Dr5BkKy6sw/Z0i2XHbZqfpLkCVxLoAnpmjGKz3c3RYEGpviPdmY8H+M8F6PYF2q9PhReM0FbhKnt/UfZ4g/AR3FJnzRWid5HHueq5FETytq0FrCe+yig4T72ZvjyfmKAbrfeqqCHI+F29JY8FT9YN4qOkqQfgJSrJS/BlaJ2nclU1ndAGalZqALqFBePTdo7JjjSSSlbr21BJgAmrs+ofxwd9zt0i71Xg8KR7JIkQQfoLWReZ8FVonccQKC/LBzK70inJHNWitSbuzq9vnqNba5rxfy00rCsursOfMFUy7t4dtfu7CygHztjreA1mpCXgqsy/T/p4UjxQjJAHFCBG+CNXHYcNf10ksfbrNyiFj9QHRwFveUuZKrAcvtADh9HEjlC1w5xzV3nNC+znXFIoODwLHcai7cVPV3FgQugfarBxGrdoPS71wiRwt7hshlDy/SQhJQEKI8FWoYjIb/rZOUg/iqLBgXYKZvUGAumOOYgHZcgKLNZCbpcq0VjjfA2rfmysoeX5TjBBB+CGuFpnzF/xpneRq+Mwc1YvpOK7GemidPu4OnOcY1zkE4IBrDc0oLK9SPF+1pQOUFC3U0+IhdA9EhQehttExIDs6PAgrfzHQ4wKXhBBBEISfw/Ig/lvxZaZjaRHr4Q0ClJ9jXkklfr/jtEvWIbW1q9S2/3A356/+aBOE+aUWUYtVTaPrmWpaQEKIIAjCz2F5EFc3tCI2Ihg1DS2UTfcTWlXCVls6wEhp+vasP1iG9QfLYI4MRdPNNlFrlFGqtFPWGEEQhJ/D+kCdOjgRgHdn02lVA0nOiga0P+RZjq+2dICR0vSFsNQ3dXCH2WNv6fIkZBEiCILwc1gfqBNSzBieFMvcC8toaBnkrGUrFrW1q/SqEWRPwk8d7XefrtTMLedpyxYJIYIgCD9HyYM4MMBk+GBmIbRu6KplJWylnedZ9tOaWaN6IfMnIRwYYMJzWQNwrKIaR8p+wPqD5S4d29OWLXKNEQRB+DlKi0jygcJTBt+O9N5dDS+CtHRj8WhdCZtv42F2akthjgqVFGli+2l5RUwA9pVYHAQvfw8kx3dx6bieLpIJkEWIIAiCwK0Hqre6vaTQ0o3FMzwpFtECKeE8aoLH1ZQOaLNyiAoLxnMT+6G6oQWxnUNgjgzFzTYrfv3eMeZzSyG1PmqtOUaKKyMhRBAEQQDwjho+anBHQ9f8UotsILCah7x96QC5gp5CMU+xEUF4cPDtGDcgHjHhQZqmqAutD4tbNTo8CCGdAhyqSxtJYJMQIgiCIGx4Qw0fpWjtxuJdbVJ0DumEcf3jBfdlEZpygd1iMU/VDa3YdOQCNh25gKgwbR/x3bqECs5fLr5p5S8GGlpgkxAiCIIgfBq1WVlisBQy/LH5JtJWFuBPD96qnMyatSYX2P3mI0OwYu9XssHRcn3FTADmjE7CruJKWOrF3w+/PjUNLR36zfHzZ3GrGlVgU68xCajXGEEYB3/r+0Voi5bNUncVX8aC7cVMY00/HRsAU78tlua2MRFBqG5wzeVlL8DarBzWHziPtQXnBc8HtAumjYcqJOdvJKsP9RojCMKn8IZGnISx0TIYXGmA8PJPS8FxHFMvMdYq364QGxGEfz07FsGd2hPHAwNMWJDZF/3MXQTXJyd7gKgFynn+rFYfI/2wISFEEISh0br+C+H7iD1ktQoGV1LIkM+4YhnDz8vdVDe04sTFmg6iRWx9XMm6E7oW+aUWQ/2wISFEEIRhUduVm/Bf5KyHWgSD2xcy1BJeLLAg1feN9Vz2OAuWnw9KtH2m1GbdCV0LsZIDnvxhQwUVCYIwLEp+iRIEbz10vmf4h2xeSaVm5+JdbbERwZod88K1Rpu1SUzW80UIX5qS6tK57AVXXkklMlYfwPR3irBgezGmv1OEjNUHbOulJutO7FqIlRxQW9hSC0gIEQRhWNxR/4XwTdxRPVquQWtWagKKFo9HbESQ6DF44WKODJGt9vxawTfIL7UwVfl+YFC7EEuIUhav5FzNmUU8sooz/phS10IKT/2wISFEEIRh0br+C+G7sFoP3z9SwSSG5KwkPMGdAvCnBwfCBGnhsmzyXUzCgHf1srTbyEpNwOFF47Btdhpmjuola51yrubMKh75feyPIXZMgK28gBR6/7ChGCGCIAyL1vVffBWlGThGytjRCtaH54q9X+HdwxWSgblKA/RZM9KeykwWTFHnsbeIsAZ28zFP6b274g/ZKbbxF641YNuxS5LVnFnF49r8cxjV5za8+chQrNgrn3XnqpDR+4cNCSGCIAyL2q7c/oTS0gK+WopAycNTKjBXbYA+i3DpFRfBND9eSCgN7HYeP39csuR8WAXL+oPlWH+wHAk/pdLHRIRIijNX+o954ocNucYIgjA0arty+wNKg4P1DCbWG7k4FnukYoZccbHxQmTK4NuR3ruraoGglUVEq/nwWOqaMG/rKdTdaBE9JnDrWijBkz9sSAgRBGF47GMh1k0bjG2z03B40Ti/FkFKg4PdEUxsJHjrIdAxjkUIscBcJS42oZghKZQGHbMiF9Stdj7OsN4n9teCFU/+sCEhRBCEVyD369bfUFpawB9KEYhZD6VwFj5qXGysYkhKrKm1iLAGdSudjxis90lWagKeyuzLeFQgJ9tzrlkSQgRBEF6I0tIC/lKKgLce5mQPYBrvLHy0crFJzU8rV68Wrk414hFgu0/mj+uD+C4hTMdbsddz1kgKliYIgvBClMab+FopgjYrh6Jvq1BYXgWAQ/qdcUj7yVIYGGDCjFFJePdwheKMQ6kAfSGk2kuIwRJYLZfZp2XVdfv5HCm7hvUHy2TfA8t9EhhgwiMjemJtwTeyY5WuoZaQECIIgvBClJYW8KVSBHkllXh+51mHKsXrD5YjOjwIq34x0NZKQ23GoVg6vBRKLWlSGWEsmX1K+3/JCSt+PsOTYrHl6EXRCtBK75NeceFM4wDPWSPJNUYQBOGFKI03cUd8ih44BwLvO1OJuVtOCj6oaxtbMdfOJeSKG8pVF5taWN1dSlydSuKI8kstoiIIaBdYSu4TJety4VoD81gtMXEc550pAjpQX1+PqKgo1NXVITIy0tPTIQiC6IAv1xESmqvJBMg9tcyRITjy/Hjbw9qVApJtVg4Zqw/IWtIOLxrnsojkzyVm6bE/17GKakx/p0j2mL8cegf+9+S/BY8FwEEQyp0fAGLCg/DF0gmK1m/Uqv0OhR3FcL5urqDk+U2uMYIgCC+GtQKx2vGeQqy6M8tPd0t9s0O8iSsd5/Us6snq7ir6tgppd3aVdHUCQIAJgiKIP5ZzHBFLa4yaxlZFsTyBASZMGZyItw9VyI51vm56Qa4xgiAIL0dpaQGjlyJQ27TTHi3jTfQq6sk653kfnpRszsojl4TlnArvjszCvJJKbGQQQWqOrRVkESIIgiAMhatNOwHts9/0sKSxzrn2RqutRYhQUHeASV4E2ZNfakF6766aZxaqEbQXrjUqGK0NJIQIgiAIQ+GqVcAcGeKW7DdXXGwsyGX2ObP801IcXjTOJtAs9U04ebEafy26pOi87x25gOFJsZiQYpY9f0x4EPPaqhG0249fwvxxfXS1UpJrjCAIgjAUrlpzlk2+y3DuPnvEWmIoaU1h79YKDDCh7kYL1uR9rVgEAbdihYD2eCcpEVbT2Ir8UovgNvv3daTsGg6f/0HxXDxR3ZwsQgRBEIShGJ4Ui9iIIFQ3iKdxC2FfR8iVTDF3Ipe1x8cjPf/JWdTekH//fHq8UGA5K/aiakKKGdHhQZJ1hIQKNQq9L7XoHSdEQoggCIIwFIEBJrw0JRVPbj0lOS42IgjT7+0BkwkOlaWNWiJATLDwNYL4wOus1AR0CQnCo5uOyh4zrnMIfr/jtEuB5TzfX28XQ3J1hJyrQLsqxJzRu7o5ucYIgiAIw/HAoEQ8PjpJdLsJwJ8eHIhns/rj9xP7Y1RynE0Eudp/yx203LRiyd9KRFtiAI49y9J6d2XqVA8OmlhhgHYBojRzTIsMPx7+Peld3ZyEEEEQBGFIFj+Qgj8/MhSxEcEOryeIpK3L9d8ClDVI1Yq8kkqkrSxAdUOL6BjnVHbWSuDXGuQLFcphL0CUZo5pkeHHo7RqtVaQa4wgCIIwLA8MSsDEVLa0daX9t9yFfXzShWsNWFtwnnlfe4uMWM8zs52br73prHqci0Iq7UmnJp5nUmo8CsurO8RARYcHKT6WFpAQIgiCIAwNa9q6OwoCKsXVoGFni4xc/SKlKffOmJ1ip5RW0lYTz9PfHIW8kqsdXq9rbHWIldILco0RBEEQPoHWBQGVIhafxIJUfIxUJXApF5ocOdkDcHjRuA6iQ0kl7eFJscyWHBPaazxtO3bJUO5LsggRBEEQPgGLdSQ6PAhWK4c2K6dpLIoWQcNq42PEXGhyxHUJcbknnVy3eh5+r+nDe0i6CvVyX9pDQoggCILwCaTcOjy1ja14dNNRzdPpXQka7hoRjD8+mOrSXOyFy5Gya1h/sEx2HznLmJxLkhd/LPAuuOabVqbxetYSItcYQRAE4TOIuXWc0TqdXu2DOzYiCIWLx2siyHjh8tSEvpKp94A2bUhYxZ+9Cy6ucwjTsVnHaQEJIYIgCMKnyEpNwOFF4/Dh70YgOkw4fkXreBSlcUcm3KqFFNxJ2aNYrEUHD0vcUNNNq2irDNbzsIo/Bxcc61LrWOGAXGMEQRA+hnN7iWE9Y3DiYo3h2k24k8AAEwJMJsk2FVrGoyjN3nLO1mKFtWq2rVXHzrOCMTxyGVos51ETnM5a90iL+kiskBAiCILwIYQeYAEmwP7HvBHaTeiBnun0LGnnCzP7oldcuGIxygvbglILNh250GG7c4sOngkpZizbXQqgoxDiIN03jKUViNKaQ4DnM/uEINcYQRCEjyCWvu3s+fF0uwm90PuhK5d2viAzWTAFXoq8kkpkrD6A6e8UCYogQNzNd6yiGpZ6tgKTPEqqc7NWv7Z/r7x4kmsdomebDbIIEQRB+ABK0relrAG+hBqLhauwpp2zoKSZqZCbT41FTGl1bpbq1/YoLdioBySECIIgfACl6dueqNeiN0Z86LKiti6RvahRYxFTI56Uij+l4sndkBAiCILwAdTGubizXotz0LYngrT1fuiyBjPLobYukb2oUWMRu3CtQfF5APY2KDxaWs5chYQQQRCED6A2zsWd7Sa0EARaoNdDlzXImAWlAlVI1Ci1iLVZObx3pEL2XFrF8CgVT+5CUbB0r169YDKZOvzNmzcPALBx40bcf//9iIyMhMlkQm1tbYdjTJ48GT169EBoaCgSEhLw61//GleuXHEYc+bMGdx3330IDQ1F9+7dsWbNmg7H2bFjB/r374/Q0FAMHDgQ+/btc9jOcRxeeOEFJCQkICwsDJmZmTh/nr0DMEEQhDchF4TqjDuDUsWCtj0ZpC3Vr0sLlAQZs6BGoAq5+ZT0DSsqr0LdjZuy53n4nu6GdCeqRZEQOn78OCorK21/+fn5AICHHnoIANDY2IisrCwsWbJE9Bhjx47Fxx9/jHPnzuGTTz5BeXk5fvnLX9q219fX42c/+xl69uyJEydO4OWXX8ayZcuwceNG25jPP/8c06dPx6xZs3Dq1ClMnToVU6dORUlJiW3MmjVr8Prrr2PDhg04evQoIiIiMHHiRDQ16Ve2myAIQi+UNN90Z3yM1oLAW1ASZMzC8KRYxEawNTONjQiStDbxBSa3zU7DummDsW12mq3Ss33RxB0nvmM6300rW5sMb8HEcZzqu3HhwoXYs2cPzp8/D5Pp1ofps88+w9ixY1FTU4Po6GjJY+zevRtTp05Fc3MzgoKC8NZbb+EPf/gDLBYLgoODAQDPP/88cnNz8fXXXwMAHn74YTQ0NGDPnj2246SlpWHw4MHYsGEDOI5DYmIinnnmGfz+978HANTV1SE+Ph7vv/8+pk2bxvT+6uvrERUVhbq6OkRGRipZGoIgCI/g6TpCheVVmP5Okey4bbPTDOEW0YpdxZexYHux7Lh10wZjyuDbmY654tMvRVPm7Zk3tjf6xndR7PITuldYmJRqxlu/Gmb7vxFiwZxR8vxWHSPU0tKCLVu24Omnn3YQQUqorq7Ghx9+iJEjRyIoqF35FhYWYvTo0TYRBAATJ07E6tWrUVNTg5iYGBQWFuLpp592ONbEiRORm5sLAKioqIDFYkFmZqZte1RUFEaMGIHCwkJmIUQQBOFtCMXD6FlZWs8ihkbCHTWLMlPMTELozYPltn+zilwlqfnOHK2ottURMlIsmFpUF1TMzc1FbW0tZsyYoXjfRYsWISIiAl27dsWlS5ewa9cu2zaLxYL4+HiH8fz/LRaL5Bj77fb7CY0Rorm5GfX19Q5/BEEQ3oZzPExwpwC3xsfYY8TKwXrgjkKBSuO+gPY4rLlbTuJ/Pv1SsD8YoD41n6e6oQXHKqpFY8Eqf5rDvjPeUbBTtRDatGkTJk2ahMTERMX7Pvvsszh16hT++c9/IjAwEL/5zW/ggodOM1auXImoqCjbX/fu3T09JYIgCK/CiJWD9UBNlWVXjikG/yR978gFTH+nCBmrD3QITlebmm+Ppb5JVkzN33YS+87cSoaSa+LqKVQJoYsXL6KgoAC/+93vVJ00Li4Offv2xYQJE7B9+3bs27cPRUXtPmWz2YyrV686jOf/bzabJcfYb7ffT2iMEIsXL0ZdXZ3t77vv2ALHCIIgiHbcIQi8hazUBLz5yFDERAQ7vC6UoaXkmEJZX6wIZepp4Zas/rFZVkxZOeDJraewruAb7DtzxdYqZMH2YlGR5glUCaHNmzejW7duyM7OdnkC1p+iz5ub2zvNpqen49ChQ2htvdUkLj8/H/369UNMTIxtzP79+x2Ok5+fj/T0dABAUlISzGazw5j6+nocPXrUNkaIkJAQREZGOvwRBEEQylCSsu1L5JVUYsXeUlQ3tNhei40IQk72AJfes3PW1/yxvZn35X76W7b7S5sFxhW3JG/Ri3USe1KsLTiPJ7eeMlQ5BXsUB0tbrVZs3rwZjz32GDp1ctzdYrHAYrGgrKwMAHD27Fl06dIFPXr0QGxsLI4ePYrjx48jIyMDMTExKC8vR05ODnr37m0TKI888giWL1+OWbNmYdGiRSgpKcG6deuwdu1a23kWLFiAMWPG4NVXX0V2dja2b9+OL774wpZibzKZsHDhQrz00ktITk5GUlIScnJykJiYiKlTp6pdK4IgCIIRI1UO1oO8kkrM3XKyw+s1Da2Yt/UU3gowuSSG7IsPFpZXYb1dgDQLlvpmrD9QhgWZybIVp3mkijBGhbELITGM0vNOsUWooKAAly5dwsyZMzts27BhA4YMGYLZs2cDAEaPHo0hQ4Zg9+7dAIDw8HDs3LkT48ePR79+/TBr1iwMGjQI//rXvxASEgKgPbvrn//8JyoqKjBs2DA888wzeOGFFzBnzhzbeUaOHImtW7di48aNuPvuu/G///u/yM3NRWpqqm3Mc889h//3//4f5syZg3vvvRc//vgj8vLyEBrqWwF6BEEQRsXdRQyNQpuVw/M7zwpuE7LIuIqaIGoAWFvwDfJKKplij2bflyRp0ePn4CpK6yu5A5fqCPk6VEeIIAiCkGNdwXmsLfhGdtxTmX2xIDNZk3PyGVsAFGV/JUSF4vCicaKp7/bjcrIHICYiRNSit+9MJZ7c2tEKpgYl9ZVYUPL8Vp01RhAEQRD+TpuVw2aG/lzALYuMFqgNora3vmSlJiAnO0VwnKWuCfO2nkLdjRZRi55zULgreLKcAjVdJQiCILwSrSsaqznesYpq1N5olRxjj5bxMPZxWAWlFqbii8CtrLE2K4cVe0sFx7DE72iRfSbULFZvSAgRBEEQXoeQW8ccGYLpw3ugV1yEJu0mWCokKxUDvEVGq/YifBxWeu+uiAwLwtoC+ebivPVFSX80ofm6asUxSjkFEkIEQRCEVyHWHsJS3+wgBFxtN8Gnd0ul/KsRA+5qLzJ/XDK2HfsOlnrh4ztbX1xth8KafSaG2SCtOChGiCAIgvAalLSHYKlTI3U8/rXln5aKZnypyeByVzxMYIAJyyanwAS2YpautkPhs89YrkVCVCj+/MhQWy2kbbPTcHjROI+LIIAsQgRBEIQXoaQ9BEuci6vuocAAE3KyU5iyp/SIh+GDqDu4DQWsL8OTYhEdHoTaRvEYp+jwIJfmO2tUL2SmmDu4KY3UsZ6EEEEQBOEVtFk5HCm7pmgfOSHjqnuIryYth57xMFoWs5Tag7emSe27r8SCJdmO79loHetJCBEEQRCGR6rmDQtiQsYV95BYbJEQauJhXLGa2Feidj6epb4J1T82o7qhRdIaBAA1ja2iIpLVmvb+kQrMGJVkq12kNh7LXZAQIgg/wUimaIJQghLBIYaY4JEL+BVzZ8nFKpkAxEYEY2n2AJijwgQ/b1KfSa2tJq4ISTERyWpNW7H3K7x7uAJ/mDQAL3z6pWg8lqfabZAQIgg/wGimaIJgRUlwtBBycTl8wO8TW05K9tZyfjCzWEOqGlpgjgoTtKZIfSYBaGo1cVVIiolIJUHflXVNmL/9lOQYOTemu6CsMYLwcfgvQaN2fiYIKZQERzvDGpcjVqXZvreWM67EFsl9Jp/feVZ1FpszrghJvtO8mIhU2/NMDneVFxCDLEIE4cPIpQYbofMz4d242+XK+lCclBqPU5fqHGroKInLURpgrDa2iCVdXypuR6nVRK2QlBOR/HWflGrGe4wVrVnRu90GCSGC8GFcTQ0mCCn0cLmyPhR/k56E9Y/EuiTKhAKMxVAbW+SKhcseV7Pd5IgOD8LKXwwUvI6uBq6L4al2G+QaIwgfxt1floT/opfLVc79Yu++4YWMWJNQLeFji/g5OM8JELamaPVZc7UYohw1IlYpseuuFZ5ot0FCiCB8GHd/WRL+iavVmJWgVnDoAR9bFB8Z4vB6fGSIaGyRFv25pOJ2nFEbx8O7ze2voauB61J0jQj2SOo8QEKIIHwaJb+mCYIVJS5XLVATzKwvYhKtIyyfyZjwINGjcABysgcoqifEC0klCF1Drdx6zsRGBKFw8XiPXUeKESIIH0ZtajBBSOEJl6uW1ZK1Qiwt/Wp9u3vwzUeGIiYiuMN85T6TK38xEABE43BW7P0KAQEmZuEg1naDBftrqLULnX+/f3pwIII7ec4uQ0KIIHwcJb2HCIIFT7lclQQzuxsW9+D8bSdh7x20DyRn+UxarRDsYaamnpC9kLTUN+HkxWr8teiS7H721zAuIkRipHKM8h1EQsjPoOrC/okRf00T3ovajClfgsVN5Bwi5SxgpD6TbVZOtIeZ2tIX9kJy8t2JKPjqe9FrCADmyBDHa6jB10VsRBByfn4XzJHG+Q4iIeRFuCpiqLqwf2OkX9OEd0MuV3VuIiEBI/aZdHfpC6lryNN004r8Uovt+XDtx2bF53FmWM8YPDjkdpePoyUULO0l5JVUImP1AUx/pwgLthdj+jtFyFh9gDlFlaoL+xZtVg6F5VXYVXwZheVVmmTnEIQSjB/A7F7Uuv1YA8n1iMPir2HUT8HZztQ1tjo8H7RwdeaXfo99Z64AMM73GFmEvABXu/VSdWHfgix7hKdwtkpPSDH7rctVzj0oh5yA0SsOa0KKGct2lwLoWDfI+fng6nvmWbqrBIAJK/Ya43uMLEIGR4t6HXqnuhLugyx7hKcQs0rnl1p0K2JoJKTqG7EgJ2D0Kn3BB0+LYf98YKnpxEJ1Qyue3Gqc7zESQgZHCxFD1YV9Az2L2BGEPSTAhRFzD0ppQVYBo1chSaXPh1tFJDu6RJ/K7OvSXDz1PUauMYOjhYih6sK+AfUNIzwBudalEcr+qmloxrytpwAoDyR3dj+++cjQDi4kLdPO1T8fHO8IjuOQ3C0CsRHBqG5oUT0fT3yPkRAyOFqIGEp19Q3Iskd4AhLg8ghlf70VYFJcu0ss/i8newBiIkLcEoc1rGcMAkwdU/3tCTC1j+PnKFxEsl38/e6+JLzzfxUuz0vP7zESQgZHCxFDqa6+AVn2CE/A+kCy1DehsLzK74KmxVBau0sqKWbe1lN461dDMWWwa2nnQiVYTlyskRRBQLtIOnGxBsOTYmWtg3vOVGK2BmJIz+8xEkIGRysRQ9WFvR+y7BGegPWBtGLPl6huuJV5RJmM7LW7Wm5aseRvZzV3P9oLnwvXGrHt2CWHwOiEqFBMSjUzHev7603M1sFx/eMxpHs0lu4q6XBPPDAwHpsOX5Q8l70FSg9ICHkBWokYqi7s3ZBlj/AErCnT9g88QF0bCG9Cqyr9eSWVWPK3kg7rZ48a96OQm80ZS10T3jtygel43bqEKnLPTxl8OyamJjis0bCeMUhbWSC7P2+BohghwgGtRAxVF/ZuyLJH6I2cABcTR74cSK1VLS8xd5gYzkJETIyxHpe/RiaJGCF7SzNriRXeiuj8vCksr5IUfPZQjBAhCIkYAiDLHqE/YgI8NiIYVRIZQr4YSO1qgVseqWw8MezdlFKB1Sv2fsV8XA4A99NgOUuzq+55JeKGYoQIgpCERDGhN0IC3FJ3A099fFp2X1/JZNSylABL01YeZ4EhJsYq65rw5E9p+0oZ3/82lFZel7Q0u+qeZxU3XSOCdY11JCFEEARBMCHk6mDBVzIZtSwloFQc8gJDjSWJhf1f/4AF4/v8VMiw/Tqn3dn+HuyzASekmFW753mLkpwAXDElVVcLNwkhgiAIQhX+lsmoZS0vVnFoMgFz7kuyCQwlliSlrNtfZvv3Jyf/jcl3J2D36UrBWKjDi8Ypds/bW5TEhNzjo5PwwCDqNUYQhsYoHZMJwtPo1QZCDr0+k1rW8pLrJWaDAzYeqrC1MdHLzVhZ14S3D1WItlVR22OOjzdLcGpLEhsRhD8/MgSLH0jR7D2wQhYhglAAdX4nCEc8ncko9Jk0R4Zi+vAe6BUXrmkygZYWMHvriBR87NEf/laCGy1tLrWv0AItsgGNlvBh4jiOfs6KUF9fj6ioKNTV1SEyMtLT0yE8jFiAIv/R9dV6KQTBglZ1dZTAmiau5Y8V/pyAcLCw0u+B9jpCZ5nTygHItsTQi22z0xxioTxxD4ih5PlNFiGCYIAaTxKENHpnMioJGtayuKPWFrCs1ATcaLXiqY+KmfcxgggCHN103mwtJyFEEAxQ40mCMBZKgoa1/rGitWvHHKkuq06qoKUe8LFQWtVW8hQULE0QDFDnd4IwFko/a/Y/VrSAt4ApDRYWgjlw2gkOwC+HutaIVQ0mtFt7hifFylrLgXYBauSkEhJCBMEAdX4nCGOh9rNmxB8rUtl3ctzX9zZsEMjCUgrreZ2zAZVYy40KCSGCYEDuF5v9LySCINyPWiuKUX+s8LFHZoWCpluXUGSlJiAnewC6hKqLdpl9Xy9EhQcxjTVHhTq4unzBWk4xQgTBAHV+Jwh9kctAkvpMCuENxR3tY48s9U1YsedLyWyymPAgDE+KRV5JJeZtPaU6Xuh/T1xGSKD0d1d0WBDefHQo0u50dAMqsZYbKavMHhJCBMGIp+ulEIS/wJqBJPaZdMabfqzYZ9+FBAbgya3idYZqGlvx0p4vsev0FZeCpmsa5VP3a2+0IsBk6rB+rLWVahqakbH6gCGzyqiOkARUR4gQwqi/agjCF1BTr8v+M3nhWgO2HbsES32zbbtRHrhKyCupxLLdpbDUG8eltG7aYEwZ3DE4W6620pzRSdh4qELXGmxKnt8khCQgIUQQBKEfbVaug9XAHt66cHjROMkfH97+Y4W1UKTePJXZFwsykwW3iVnxcrJTsGKvuMWO9ZoqhQoqEgRBEF6HVvW69C7uqCXu6i4vhTkyBABwtb5Z8ryvFXyDfubOgtYbsdpK3lCDjbLGCIIgCEPgCxlIruLO7vJiTB/eAy/8PIVJfAnVBOKb3u45cwUA8PNBibbaSt5wTckiRBAEQRgCX6vXpcZF5wlBsLbgPBKiQpE90Iy9Zy2i44SsN0KxTObIUCyb3B6TFRcRwjQHT15TEkIEQRCEIdCyu7unUdt7y12CwATg/43rg6Jvq3DsQk2H7ZV1TZIiyB5erOWVVGLulo5ZbZb6JszdchKPj07CruJK2eOZI0M8ek3JNUYQBEEYAqkKy96UAs8HOzu7uPjeW3kl4uKgpqFFcZFIOTqHdMLY/rdhy9FLgiJIKXxNoOd3npUc9/ahCqast6abVuSXsokwd0BCiCAIgjAMYhWWnSsaewI+FmZX8WUUllcJ9s9ypfdWe2FE7bPFfmy+iQNf/4DqhhaXjmNfQb/o2yrUMtQfYqG2sVVWILoTco0RBEEQhkLr7u5awOrqUpslpTRbzGQCPFH8hrfIFZZXaX7s5Z+WYkKKWffrTBYhgiAIwnBo2d3dVZS4utRmSSnNFuM4IDYiGOP738a8jytEhwc5WeS0VWGebM5KQoggCIIgRFDq6lKb+aYmW6ymoQUHvv4Bj49Ocrn7vBxvTr8lgtqsHKLC2Jq0KsUTsULkGiMIgiAIEZS6utRmvqnJFuN+Ot7u05X417NjceJiDb6/3oTzV69j/cFyxccTwxwZgjS7dHm53m6u8N6RCxieFKtrLBhZhAiCIAhCBKWuLrWZb7yAUuoA5IXYiYs1NlfiqD7aussy+sRhz5krWFdwXtBFqCUmiAeTuwtFQqhXr14wmUwd/ubNmwcA2LhxI+6//35ERkbCZDKhtrbWYf8LFy5g1qxZSEpKQlhYGHr37o0XX3wRLS0tDmOEzlFUVORwrB07dqB///4IDQ3FwIEDsW/fPoftHMfhhRdeQEJCAsLCwpCZmYnz588rebsEQRCEn8NqqblwrdH2bzWZb1ICigV7wcaLKq3435OXsWB7MdYWfMMUGeRKNJcnYoUUCaHjx4+jsrLS9pefnw8AeOihhwAAjY2NyMrKwpIlSwT3//rrr2G1WvH222/jyy+/xNq1a7FhwwbB8QUFBQ7nGjZsmG3b559/junTp2PWrFk4deoUpk6diqlTp6KkpMQ2Zs2aNXj99dexYcMGHD16FBEREZg4cSKamny3NDtBEAShLcOTYm29uKTYfvySgxUjKzUBhxeNw7bZaVg3bTC2zU7D4UXjJF0+YgKKBXvBFhhgwuS7PVNmICd7AN58ZAhMcE0Q6Vlh26Xu8wsXLsSePXtw/vx5mEy33vJnn32GsWPHoqamBtHR0ZLHePnll/HWW2/h22+/BdBuEUpKSsKpU6cwePBgwX0efvhhNDQ0YM+ePbbX0tLSMHjwYGzYsAEcxyExMRHPPPMMfv/73wMA6urqEB8fj/fffx/Tpk1jen/UfZ4gCEI53t793Zl1Bd9gbYG8R2Hb7DRNGofar19c5xA883GxaENUoe7tbVYOGasP6N6zDADWTRuMKYNvdzmWyNW11KX7fEtLC7Zs2YKnn37aQQQppa6uDrGxHUtrT548GU1NTejbty+ee+45TJ482batsLAQTz/9tMP4iRMnIjc3FwBQUVEBi8WCzMxM2/aoqCiMGDEChYWFokKoubkZzc3Ntv/X19erfl8EQRD+iNrWEkamV1wE0zitrBh86QCeZZPvwhNbTsIEx6R1sZgjTzRu5eEtU3wtqKLyKszbehK1N9iKL3qijYrqYOnc3FzU1tZixowZqk9eVlaGN954A48//rjttc6dO+PVV1/Fjh07sHfvXmRkZGDq1KnYvXu3bYzFYkF8fLzDseLj42GxWGzb+dfExgixcuVKREVF2f66d++u+r0RBEH4G660ljAynm4GqzTmyBONW+2rTvMEBpgwKjkOf3owlfk4HPRvo6LaIrRp0yZMmjQJiYmJqva/fPkysrKy8NBDD2H27Nm21+Pi4hysPffeey+uXLmCl19+2cEq5A4WL17scO76+noSQwRBEAzI1dvhs4E8UTnYVdzRDFap+1BJtW29O7lLZcPllVRixd6vmI8VEx6ECSlmDWcnjyohdPHiRRQUFGDnzp2qTnrlyhWMHTsWI0eOxMaNG2XHjxgxwhaYDQBmsxlXr151GHP16lWYzWbbdv61hIQEhzFicUcAEBISgpAQ+aA4giAI4hZtVg7vH6lQ1VrCG+AzupS4p6RQ6z50dpmJISfctCYqPAirfjGww9x5C6GSOdQ0tup+j6hyjW3evBndunVDdna24n0vX76M+++/H8OGDcPmzZsRECA/heLiYgdBk56ejv379zuMyc/PR3p6OgAgKSkJZrPZYUx9fT2OHj1qG0MQBEG4Tl5JJTJWH2D+1e8Jt40anBusTkgxa9IMVg/3oaup+EoJCwrsYMVR2jvNHr3vEcUWIavVis2bN+Oxxx5Dp06Ou1ssFlgsFpSVlQEAzp49iy5duqBHjx6IjY21iaCePXvilVdewQ8//GDbl7fifPDBBwgODsaQIUMAADt37sR7772Hd9991zZ2wYIFGDNmDF599VVkZ2dj+/bt+OKLL2zWJZPJhIULF+Kll15CcnIykpKSkJOTg8TEREydOlXpWyYIgiAEUPOLX2+3jRqkLDaHF41TnRGnp/uQjyta8rcSl7vOyyFk6XMlYFvve0SxECooKMClS5cwc+bMDts2bNiA5cuX2/4/evRoAO0WpBkzZiA/Px9lZWUoKyvDHXfc4bCvfRb/ihUrcPHiRXTq1An9+/fHRx99hF/+8pe27SNHjsTWrVuxdOlSLFmyBMnJycjNzUVq6q2ArOeeew4NDQ2YM2cOamtrkZGRgby8PISGGv9DSBAEYXRablqx5G9n2bulQ/9sIDWIiTveYqPE+uOM2s70aslKTcCNljY89fFpl48lx5Gyaw7iUK1VxzngWg9cqiPk61AdIYIgiI7klVQqsjTwcTUzR/XChBSzYesKydXfEarZo4Rdxe0VmuXga/EIzU+pNaqwvArT3ymSHKM1CVGhmHZvd6baS848PjoJix9IcXkOutQRIgiCIPwPNe4wkwnguPaGmu8duWDYukLutti4koavNsBa78BpoN16trbgPKLDg1DbyFY/iGf36Uo8lzVAV6FMTVcJgiAIJtQGwDr3zzRqXSGlDVaVItdYVagWD+BagLXegdPArXgnNejdZwwgIUQQBEFIYJ89JZcib48JgNiPel4X6d1lXA53F05U05leLsAaEF5H++sWFRaMNx8ZoqqHmVo4ALWNrVg4PhmhQcqkhuGzxgiCIAj/wJV+URza3WFS241WV8gdhROd4bO5nNfVLOLmUuOuE3Oj/XxQAj45+W9UNyhzV7nC+59fQFOrVdE+hs8aIwiCIHwfNbFAPLERQZg6+Ha8d+SC7Fgj1RXSunCiGEqqRLOuT0GpBem9u4pet8q6JrzzfxUuzVsNrD3GAM9lFpIQIgiCIBxwpRhe14hgFC4ejxMXa5iEkNHqCim12KiFtUo06/psOnIBnUM74YPPL+oWFK0lWgpNpZAQIgiCIBxQUwyPf3T98cFUBHcKYHIzxUYEw1J3A4XlVYZKqVdisRFCTZq7GEqyvtbtL1N1DiNgMgGz70vySCYhCSGCIAjCATXuKmeLiZSbCT/9v6qhxVbsz90p9UrFCavFxhm1ae5S83jxP1Iwd8tJxft6E1YO2HioAkN6xOguhqigogRUUJEgCH+EtQhfTvYAxHUJkRQWrAHX/J5KKjezihtXxIkSASUWn6PmvTnzP59+yeRqdBcLxydj3f72AonuFA0JLhSstIcKKhIEQRCqYc2emjEqSfaBZe9mstQ3YcWeLwWzlpT22mIVN660zFAioNzdRywyNEjxPloRYAIeH9Mb/RO6yIpa3voXHR6EusZWxaLJE5mEVEeIIAiCcEBNvRu546X37gpzZKhk6rZ9KrgUrAUG1dbgkTpHpUgRQyVp7s44d7rn58O/vmx3CdYdUN6uQiusHDBq9X4AwOFF47BtdhrWTRuMpzKTYY4McRhrjgrFhl8NxapfDASgrrCipe6Gq1NWBFmECIIgiA64I3tKi8rNSiwvrOLk/SMVDi4+/HQMMWsGB2DxzrMO1h3W9+b8kBezOk2+OwG7T1eq7uCuNdUNrYIWtPnjkkVdh0L3D9u52HrYaQUJIYIgCEIQV7OnnNGicrMSywurOFmx9yvbv/mGoXIP75rGVqw/cB4LMvvKztn5XGHBgchKTZCs+fP2IW1q/ggFqquFQ0f3Hm/t42Op9py5YrtPnO+fc5XX8ed/lcueJyY8WKMZs0FCiCAIghBFbfaUEFpUblZiVVJTo4hvGMrC5iMXMH9cMgIDTMxp7jUNLXhiy0m8+chQrNirrlaTErQ+fmVdE9bmf4NRfeJsolguloq/fzZd/5bpHDWN+lqEKEaIIAiC0AUtYo9Yxc21680Y1jNGssmpEEqEQ+2NVhyrqLZZQx5INcvuz2/P2VXiVrdXgAmYMbKnW469/mAZpr9ThHv/WID5H57EXMaGsLERbJYe1nFaQUKIIAiCEEUskFctfOyRcwNQc1QoU3q5XAd3nhV7v8KYlw9i8t3tx3NXqcb8UgsyVh/A9HeKsOmn9HaTzMn4GkruxMoBPza1ufUc1Q0t2HO2UnCbUDC6OSqM6bis47SC6ghJQHWECILwZ7QuDmiPK9WX+dgaQNqCwx9tzugkQwUe+xvbZqfZ4ogyVh+QvA4x4UH4YukEXesIkUWIIAiC6ABrirpa+NijKYNvR3rvrooefGJWJWd4kbT7dCX+9exYW9p3TvYApvN0DgmU3G6QjiCGxz6ua1jPGMmxNY2tyC+1uHtKDpAQIgiCIBxwpf6OXmSlJuDwonGyoobPIjtxscYmvGaMSpJ0r5nQbvla85+DRLcD7e4nTyHnfjMS3bqEIq+kEqNW7ceeM/ICWu97i4QQQRAE4YArxQH1JDDAhLguIfID4WiVYA3afmBQIjb8aigSBOKZZo3qpWrOWuiXrhHBeH3aELfFPWkFLyhrGprxxJaTsNQ3M+2n971F6fMEQRCEA1oUPtQCljgitbWJWApGtlk5RIUF47ms/qj+sRmxEcEwR4VheFIsjlVU24KjpYgIDkRDy62gZfNPdYpYU/Tt4d/5Hx9MRVZqAgJNJszfdtKjlik5crJTVJUJcPe9ZQ8JIYIgCMIBLQofugproDafRSZlwUoQqU0kVTBS7Pw52SntfdPqbiA2Ihg1DS2SD3leBEWHBeG3o3ph/rhkAMD2499J1lOKDg9CSKcABysKL9ImpJhRWF6F0sp6Q4ugOaOTEBMRrCpI3Z33ljMkhDyAK9kSBEEQ7kaLwoeuoKRRamCACZPvTpCsxDz57gTR71ihgpFSFZ+f3HpS6dsBANTdaMVrBefRz9wFWakJePE/UvDElpMdKj/zs1z5i4GCIo1P1/eGDLgdJ/6Nbyz1ivcTE67ugmKEdCavpNJWc2LB9mJMf6cIGasPuJyBQRAEoRVaN11VgtJA7TYrh92npb8/d5+uZA6+lTq/KzjPnaWeknNmXX6pRTCTz6hUN7Ti4DdVivdz170lBgkhHXF3OipBEIRWuFr4UC1KA7XlxgPKgm9ZjidEbEQQ5o3tLTmGn3vRt+3igM9849P6t81Ow+FF4wTX1l0CrUuosRxDT2X2ddu9JYaxVsCHUdIxmdxkBEFogatueK2brrKgNFBb68ButUG61Q2tMDHmcc378CRW/edAB6uPHGoFmhzXm25Kbteyaasc5sgQzB/XR6ez3YKEkE4o+ZWjVYNDgvAEFANnDLSqCq1l01UWlAZqax3Y7VqQLptkqL3R2iHWSQ49s6js0TMWe9nkuzzyXUFCSCeMko5KEO7EnS0ZCHaUBBsbDaWB2loHdrN2kRciMMCkaF8lXgA9s6g8QecQz8kRihHSCSOkoxKEO6EYOGPgDVWhpVASqM1bHyf91PVdi8BuqfPL8dHx75CTncI0VmlRStZms97Kj803PfY9QUJIJ+RuYr4Cp54pgwShFd7+8PUlvKUqtBQsgdr2GbjviXR9VxvYzdrLzBlLfTNiIoLx1q+GIjosiGkfVi+AKwLNm/DE9wS5xnSCv4ml6kbonTJIEFpBMXDGwVfc8HLFDoVcf/zzc9aoXshMMbsUn+Z8/vNXr2P9wXLZ/b6/3oQpg29Hl5AgPLrpqOx4JV4AsWrYvoKnvifIIqQjnkpHJQh34ysPX1/Al9zwQh3qWdLI95VYNAnStz//qD63Me1z4VojACCtd1e3eAHsU+5/k95T0b56oMVveb2/J8gipDOeSEclCHfjSw9fb8fTVaHdjZK6QVpaFYYnxcIcGSLbOHT78UuYP66PS14AucxL+0y+vxRelJ37/LG9ERMejBV7v5Id6yrrpw9BZV2TS+fS+3uCLEIeQOhXDkF4MxQDZxw8WRVaD1itBfmlFk3PGxhgwvThPWTH2cdfqfECCHUfuPePBfifT79EYXkV2qwc2qwcCsur8I8vKzvERdnDf+6emtAPcV1CFL1fpYQGBWDDr4ZiYmoCahpbVB3DU98TZBEiCMJlKAbOWLB0VvdWWK0Fu4qv4A/Zyu45OUtMr7gIpuMcKfvBtq8SL4BY7FN1QwveO3IB7x25gOjw9iDs2sZWprnwnzt3W1n+NHUgALjcB80T3xMkhAiC0ARffvh6I77qhh+eFIvYiCBUN0gLgaqGFkXuMZYaWKxiYv3Bcnxy8rJtX5ailKwtNFgFUIAJWD/9ltXJlfpILHxX04jXCs6rPrYn642RECIIQjN89eHrrehdFVoPAgNMeHDw7dj0U8q8FKxuNNYClDUN0vFBUvvKoXULDSsHxEQE2/7PW23nbjmp2Tl4EqJCse3YJUUiaMbInugeE47YziEwR3r2e4KEEEEQmuKLD1/CWGSmmJmEEIsFh7UP5Lj+8YoCgJX2kHRHppT9MdusHM5ZfpQc//joJPy18BIaW9sUned6Uyt+bGbbJ8AEzL4vCYsfYCs8qQckhAiC0A3qQ0ZogauZcfb34bXrzUw1sP5aeEGxxca5Lo7U/e+OGB7+mHkllVi2+0vZjLfdpyuxcHwy/pT3taLzsIogAOA4YOOhCgzpEWMYdzkJIYIgdIH6kBH2uCKKXQnOF7oPWbhY3ahovD3fX2+Svf+H9YxBgOlWUUhXCTABw3rGiLr9hKisa8KAxEhN5+GMUkuZHpAQIgjC7XhzE1BCe7QQxWqC85WIAmd6xoar2KudC9caBAOJK+uaMHfLSTyVmYx7esZqKj6sHHC8opopANueg+e+x+z7kvD2oQrtJuOE0SrNkxAiCD9Db/cUawyGUX4d+hJGdEWKiZFboqCvrSChHEqC81mzspzh3Wy/Tu+Fdw9XKM66igkPwtajFyX3WVtwHlGMvcmU8EFhhWLL167iK1gx5S6EBwegscWq+ZzsMUqleRJCBOFHeMI9RX3IPIPUtfZUZh+LGFlb8A22HbuIZZPvYronAwNMGJ4Ua3s/xyqqMaxnDE5crHF4f2qysuzdbMGdAkTdcVLcaGlDzU15QVF3gy0tPiIkEADQwBCX88/S75mOaU9VQwue3HpK8X48sRHBqG5gK6gYF+HeIo+skBAiCD/BU+4p6kOmP1LXeu6Wk4gOD3KoR6NXrBarGLHUNzPfk0KCzznGJSEqFA+kmhXP19nNpqbpaRODCGIlNiIYRYvHAwDSVu5nFhx6kRAVin89OxbHK6oxb+tJ1MqIu2d2nMayyZ6PEaQWGwThB8i5p4B291SbGyIkqQ+ZvrBca+eifLwYziupdOvclIpduXuSF3zOosR5F0tdE1O6PQDkZA/AummDsW12Gg4vGtfhIc03Pc3JHsB0PC0Z1+82BAaYENwpAH96MBUmdGyj4kmm3dsdgQEmjEqOw8P33iE7/mq9PvedHCSECMIPUOKe0hrqQ6YvalxA7hbDPErErtw9qSTmhx8TYBIXDvx9OGNUkmwfyMAAk9t7dwnxvycvI2P1AeSVVIr2MfMkawvOI2P1Aew7cwW7T8uLG73uOzlICBGEH+BJ95SvNwE1GmqvoTvFMI+cKBZC7P2oEXxW7laAvj1q7kNPWTDtrXe8dWrb7DSM6Rvnkfk4Y6lrwpNbTzFfGz3uOzlICBGEH+Bp95SaLtyEOly9hu6M1QoMMGHy3QmKsq7E3o/aec4c1UuT+5AXdXrjbEXhg8XP/LtOk+PHRriWvabWrlNQanHpvK5AwdIE4Qe4WolXC6gPmT642lzTnZaOvJJKbGSsTyN3T6qd54QUM/6QneLyfWhf1FFsnYM7BaBFw2BpHudMy2MV1ahhbMYqB2sfN635W/FlLMn2jGWYLEIE4QcYxT3F9yGTi8Eg1CN1raVwd6yWkpgelntyeFIsohXU3rF/f1rdh7yl09ky1DUiGG9MH4Lw4EBFxwsPDoQ5kl3g8VYxS90NReeRIjPFjKcykzU7HivVDa0ec4+RECIIP4HcU/6D2LWODm8XDp4Qw0pieljuycAAE347KknRHNzx/uzjdPhss2N/yERc55AO2XlyNLa04dWH7mbOSOOtYlqk0dsLxfnjkhUJMq3wVAkNco0RhB9B7in/Qexa55daFLWl0ArWh9z8sb3x1IR+TPfk/HF9sPnzClnB4e46SbyFyR61D/VrDc2YMSpJsoq1s9swtrNrGWxCQnjZ5Ha3H9CxlxuHdlFd19gqauFT06/MUwHoJIQIws8Q+tImfBOha+0pMcz6kBvV5zZFzVdX/WIg5v70wBbiqcxkzB+XrLvYV/tQ79YlVHFTWVetN0JCWK6XGwDJ+c2+LwkbD1Uwx6l5soQGCSGCIAg/wxNi2F0B+1mpCdgg8MDWq1q2GEqD1p3fv5Kmsvy5lJQT6BoRjKXZA2COChMVwnKiWW5+Q3rE4PmdZ2UtdiZ4toSGieM4z1UxMjj19fWIiopCXV0dIiMjPT0dgiAIr4avBA0IWxFciVUzcoNZQDqtXOr9s74v1nPx59MqLlBufm1WDusPnMfmIxcEW264S7AqeX6TEJKAhBBBEIS2eKLxrydh7YWmxfsXOpfJBHBuOJdSeMFkqW9C9Y/NiI0IlrRGuYqi5zengJ49e3JoF5sOf08++STHcRz39ttvc2PGjOG6dOnCAeBqamoc9q+oqOBmzpzJ9erViwsNDeXuvPNO7oUXXuCam5sdxp0+fZrLyMjgQkJCuDvuuINbvXp1h7l8/PHHXL9+/biQkBAuNTWV27t3r8N2q9XK5eTkcGazmQsNDeXGjx/PffPNN0reLldXV8cB4Orq6hTtRxAEQYhzs83KfV52jcs99W/u87Jr3M02q6en5Fac329za5vb3r+e5zIySp7fimKEjh8/jra2Ntv/S0pKMGHCBDz00EMAgMbGRmRlZSErKwuLFy/usP/XX38Nq9WKt99+G3369EFJSQlmz56NhoYGvPLKKzYV97Of/QyZmZnYsGEDzp49i5kzZyI6Ohpz5swBAHz++eeYPn06Vq5ciZ///OfYunUrpk6dipMnTyI1NRUAsGbNGrz++uv44IMPkJSUhJycHEycOBGlpaUIDTVObxaCIAh/w98C9oXer7vev57n8hlcUVwLFizgevfuzVmtjgrz4MGDghYhIdasWcMlJSXZ/v/nP/+Zi4mJcbASLVq0iOvXr5/t///1X//FZWdnOxxnxIgR3OOPP85xXLs1yGw2cy+//LJte21tLRcSEsJt27aN+f2RRYggCIIgvA8lz2/VBRVbWlqwZcsWzJw5EyaTev9eXV0dYmNvZQkUFhZi9OjRCA4Otr02ceJEnDt3DjU1NbYxmZmZDseZOHEiCgsLAQAVFRWwWCwOY6KiojBixAjbGCGam5tRX1/v8EcQBEEQhO+iWgjl5uaitrYWM2bMUH3ysrIyvPHGG3j88cdtr1ksFsTHxzuM4/9vsVgkx9hvt99PaIwQK1euRFRUlO2ve/fuKt8ZQRAEQRDegGohtGnTJkyaNAmJiYmq9r98+TKysrLw0EMPYfbs2WqnoSmLFy9GXV2d7e+7777z9JQIgiAIgnAjqgoqXrx4EQUFBdi5c6eqk165cgVjx47FyJEjsXHjRodtZrMZV69edXiN/7/ZbJYcY7+dfy0hIcFhzODBg0XnFRISgpAQ10qVEwRBEAThPaiyCG3evBndunVDdna24n0vX76M+++/H8OGDcPmzZsREOA4hfT0dBw6dAitrbcKL+Xn56Nfv36IiYmxjdm/f7/Dfvn5+UhPTwcAJCUlwWw2O4ypr6/H0aNHbWMIgiAIgiAUCyGr1YrNmzfjscceQ6dOjgYli8WC4uJilJWVAQDOnj2L4uJiVFdXA7glgnr06IFXXnkFP/zwAywWi0PcziOPPILg4GDMmjULX375JT766COsW7cOTz/9tG3MggULkJeXh1dffRVff/01li1bhi+++ALz588HAJhMJixcuBAvvfQSdu/ejbNnz+I3v/kNEhMTMXXqVMWLRBAEQRCEj6I0Je0f//gHB4A7d+5ch20vvviiYMHFzZs3cxzHcZs3bxbc7jwN+4KKt99+O7dq1aoO5/r444+5vn37csHBwdxdd90lWlAxPj6eCwkJ4caPHy84ZykofZ4gCIIgvA8lz29qsSEBtdggCIIgCO9DyfObus9LwGtEqidEEARBEN4D/9xmsfWQEJLg+vXrAED1hAiCIAjCC7l+/TqioqIkx5BrTAKr1YorV66gS5cuLlXP9jbq6+vRvXt3fPfdd37vEqS1cITW4xa0FregtbgFrcUtPLkWHMfh+vXrSExM7JCd7gxZhCQICAjAHXfc4elpeIzIyEi//yDz0Fo4QutxC1qLW9Ba3ILW4haeWgs5SxCP6srSBEEQBEEQ3g4JIYIgCIIg/BYSQkQHQkJC8OKLL1K7EdBaOEPrcQtai1vQWtyC1uIW3rIWFCxNEARBEITfQhYhgiAIgiD8FhJCBEEQBEH4LSSECIIgCILwW0gIEQRBEATht5AQ8gFWrVoFk8mEhQsX2l5ramrCvHnz0LVrV3Tu3Bn/+Z//iatXrzrsd+nSJWRnZyM8PBzdunXDs88+i5s3bzqM+eyzzzB06FCEhISgT58+eP/99zuc/80330SvXr0QGhqKESNG4NixYw7bWeaiFUJrcf/998NkMjn8zZ0712E/X1iLZcuWdXif/fv3V3RuX1gHHrn18Jf7gufy5cv41a9+ha5duyIsLAwDBw7EF198YdvOcRxeeOEFJCQkICwsDJmZmTh//rzDMaqrq/Hoo48iMjIS0dHRmDVrFn788UeHMWfOnMF9992H0NBQdO/eHWvWrOkwlx07dqB///4IDQ3FwIEDsW/fPoftLHNx51rMmDGjw72RlZXlc2vRq1evDu/TZDJh3rx5APzoO0PbxveE3hw7dozr1asXN2jQIG7BggW21+fOnct1796d279/P/fFF19waWlp3MiRI23bb968yaWmpnKZmZncqVOnuH379nFxcXHc4sWLbWO+/fZbLjw8nHv66ae50tJS7o033uACAwO5vLw825jt27dzwcHB3Hvvvcd9+eWX3OzZs7no6Gju6tWrzHNx91qMGTOGmz17NldZWWn7q6ur87m1ePHFF7m77rrL4X3+8MMPzOf2lXVgXQ9/uS84juOqq6u5nj17cjNmzOCOHj3Kffvtt9w//vEPrqyszDZm1apVXFRUFJebm8udPn2amzx5MpeUlMTduHHDNiYrK4u7++67uaKiIu7//u//uD59+nDTp0+3ba+rq+Pi4+O5Rx99lCspKeG2bdvGhYWFcW+//bZtzJEjR7jAwEBuzZo1XGlpKbd06VIuKCiIO3v2rKK5uHMtHnvsMS4rK8vh3qiurnY4ji+sxffff+/wHvPz8zkA3MGDBzmO85/vDBJCXsz169e55ORkLj8/nxszZozt4V9bW8sFBQVxO3bssI396quvOABcYWEhx3Ect2/fPi4gIICzWCy2MW+99RYXGRnJNTc3cxzHcc899xx31113OZzz4Ycf5iZOnGj7//Dhw7l58+bZ/t/W1sYlJiZyK1euZJ6LFoitBcdxHf7vjK+sxYsvvsjdfffdgtv88Z6QWg+O85/7guM4btGiRVxGRobodqvVypnNZu7ll1+2vVZbW8uFhIRw27Zt4ziO40pLSzkA3PHjx21j/v73v3Mmk4m7fPkyx3Ec9+c//5mLiYmxrQ9/7n79+tn+/1//9V9cdna2w/lHjBjBPf7448xzcQW5teC4diE0ZcoU0e2+shbOLFiwgOvduzdntVr96juDXGNezLx585CdnY3MzEyH10+cOIHW1laH1/v3748ePXqgsLAQAFBYWIiBAwciPj7eNmbixImor6/Hl19+aRvjfOyJEyfajtHS0oITJ044jAkICEBmZqZtDMtctEBsLXg+/PBDxMXFITU1FYsXL0ZjY6Ntmy+txfnz55GYmIg777wTjz76KC5dusR8bl9aBx6x9eDxl/ti9+7duOeee/DQQw+hW7duGDJkCN555x3b9oqKClgsFoc5REVFYcSIEQ73R3R0NO655x7bmMzMTAQEBODo0aO2MaNHj0ZwcLDDepw7dw41NTW2MVJrxjIXd64Fz2effYZu3bqhX79+eOKJJ1BVVWXb5itrYU9LSwu2bNmCmTNnwmQy+dV3BjVd9VK2b9+OkydP4vjx4x22WSwWBAcHIzo62uH1+Ph4WCwW2xj7m5ffzm+TGlNfX48bN26gpqYGbW1tgmO+/vpr5rm4itRaAMAjjzyCnj17IjExEWfOnMGiRYtw7tw57Ny5U/J98tukxhhpLUaMGIH3338f/fr1Q2VlJZYvX4777rsPJSUlfndPANLr0aVLF7+5LwDg22+/xVtvvYWnn34aS5YswfHjx/Hf//3fCA4OxmOPPWY7j9A87d9rt27dHLZ36tQJsbGxDmOSkpI6HIPfFhMTI7pm9seQm4sryK0FAGRlZeEXv/gFkpKSUF5ejiVLlmDSpEkoLCxEYGCgz6yFPbm5uaitrcWMGTNs5/aX7wwSQl7Id999hwULFiA/Px+hoaGeno5HYVmLOXPm2P49cOBAJCQkYPz48SgvL0fv3r31mqrbmTRpku3fgwYNwogRI9CzZ098/PHHCAsL8+DMPIPUesyaNctv7gsAsFqtuOeee/CnP/0JADBkyBCUlJRgw4YNtoe/v8CyFtOmTbONHzhwIAYNGoTevXvjs88+w/jx4z0yb3ezadMmTJo0CYmJiZ6eiu6Qa8wLOXHiBL7//nsMHToUnTp1QqdOnfCvf/0Lr7/+Ojp16oT4+Hi0tLSgtrbWYb+rV6/CbDYDAMxmc4eIe/7/cmMiIyMRFhaGuLg4BAYGCo6xP4bcXFxBbi3a2to67DNixAgAQFlZmeT75LdJjTHSWjgTHR2Nvn37oqysjOncvroOPPbrIYQv3xcJCQlISUlxeG3AgAE2VyF/Hrl5fv/99w7bb968ierqak3uIfvtcnNxBbm1EOLOO+9EXFycw73hC2vBc/HiRRQUFOB3v/ud7TV/+s4gIeSFjB8/HmfPnkVxcbHt75577sGjjz5q+3dQUBD2799v2+fcuXO4dOkS0tPTAQDp6ek4e/asw4c5Pz8fkZGRti+J9PR0h2PwY/hjBAcHY9iwYQ5jrFYr9u/fbxszbNgw2bm4cy0CAwM77FNcXAyg/QvRl9bCmR9//BHl5eVISEhgOrevrgOP/XoI4cv3xahRo3Du3DmH17755hv07NkTAJCUlASz2ewwh/r6ehw9etTh/qitrcWJEydsYw4cOACr1WoTkenp6Th06BBaW1sd1qNfv36IiYmxjZFaM5a5uHMthPj3v/+Nqqoqh3vDF9aCZ/PmzejWrRuys7Ntr/nVd4bL4daEIXDOgJk7dy7Xo0cP7sCBA9wXX3zBpaenc+np6bbtfNrjz372M664uJjLy8vjbrvtNsG0x2effZb76quvuDfffFMw7TEkJIR7//33udLSUm7OnDlcdHS0QxaB3FzcuRZlZWXc//zP/3BffPEFV1FRwe3atYu78847udGjR/vcWjzzzDPcZ599xlVUVHBHjhzhMjMzubi4OO77779nOrevrAPLevjTfcFx7aUlOnXqxP3xj3/kzp8/z3344YdceHg4t2XLFtuYVatWcdHR0dyuXbu4M2fOcFOmTBFMnx8yZAh39OhR7vDhw1xycrJDynhtbS0XHx/P/frXv+ZKSkq47du3c+Hh4R1Sxjt16sS98sor3FdffcW9+OKLginjcnNx11pcv36d+/3vf88VFhZyFRUVXEFBATd06FAuOTmZa2pq8qm14Lj2DK0ePXpwixYt6rDNX74zSAj5CM5C6MaNG9yTTz7JxcTEcOHh4dyDDz7IVVZWOuxz4cIFbtKkSVxYWBgXFxfHPfPMM1xra6vDmIMHD3KDBw/mgoODuTvvvJPbvHlzh3O/8cYbXI8ePbjg4GBu+PDhXFFRkcN2lrloif1aXLp0iRs9ejQXGxvLhYSEcH369OGeffZZh3oxHOcba/Hwww9zCQkJXHBwMHf77bdzDz/8sENtFH+7J6TWw5/uC55PP/2US01N5UJCQrj+/ftzGzdudNhutVq5nJwcLj4+ngsJCeHGjx/PnTt3zmFMVVUVN336dK5z585cZGQk99vf/pa7fv26w5jTp09zGRkZXEhICHf77bdzq1at6jCXjz/+mOvbty8XHBzM3XXXXdzevXsVz8UVpNaisbGR+9nPfsbddtttXFBQENezZ09u9uzZDg9lX1qLf/zjHxwAwWP6y3eGieM4znW7EkEQBEEQhPdBMUIEQRAEQfgtJIQIgiAIgvBbSAgRBEEQBOG3kBAiCIIgCMJvISFEEARBEITfQkKIIAiCIAi/hYQQQRAEQRB+CwkhgiAIgiD8FhJCBEEQBEH4LSSECIIgCILwW0gIEQRBEATht5AQIgiCIAjCb/n/ATvw6aFPfDraAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING UP UNDERPOPPED\n",
    "HDnAddedUnits, HDaddedPop = [0]*nHDs, [0.]*nHDs\n",
    "underPoppedList = list()\n",
    "minDistrictPop, maxDistrictPop = 0.99 * aDP, 1.01 * aDP\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop < minDistrictPop and t in popHDlist:\n",
    "        underPoppedList.append(t)\n",
    "print(\"We will now square up the\",len(underPoppedList),\"HDs with pop <\",int(minDistrictPop),\"to within\",int(maxGap) )\n",
    "startTime = time.time()\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "for ii,t in enumerate(underPoppedList):\n",
    "    if ii%100 == 0:\n",
    "        print(\"working on squaring up HD\",t,\"time is now\",int(time.time() - startTime)) \n",
    "    gap = aDP - HDvPop[t]\n",
    "    origGap = gap\n",
    "    nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "    for u in HDunitList[t]:\n",
    "        for uu in unitNbrs[u]:\n",
    "            if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap:\n",
    "                nearHDlist.append(uu)   #below line: bias toward close, underused\n",
    "                nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  \n",
    "    currList = HDunitList[t].copy()\n",
    "    addedList = list()\n",
    "    stillGoing = True\n",
    "    while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "        idx, i, notYetPicked = np.argsort(nearHDscore), 0, True\n",
    "        while i < len(nearHDscore) and notYetPicked:        \n",
    "            listNo = idx[i]   #nearHDscore.index(np.min(nearHDscore))\n",
    "            unitNoToAdd = nearHDlist[listNo]  #add this unit ...\n",
    "            canAdd  = wontEnclave(unitNoToAdd, currList, unitNbrs, borderUnits)\n",
    "            if canAdd: \n",
    "                notYetPicked = False\n",
    "            else:\n",
    "                i +=1\n",
    "        if notYetPicked:\n",
    "            stillGoing = False  #can't add any more units without creating an enclave\n",
    "        else:\n",
    "            gap -= unitPop[unitNoToAdd]\n",
    "            addedList.append(unitNoToAdd)\n",
    "            currList.append( unitNoToAdd)\n",
    "            for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                if uu not in currList and uu not in nearHDlist and unitPop[uu] < gap + maxGap:  \n",
    "                    nearHDlist.append(uu)\n",
    "                    nearHDscore.append((unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )  #bias toward close, underused\n",
    "            del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "            del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "            for i, uu in enumerate(nearHDlist.copy()):\n",
    "                if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                    del nearHDscore[nearHDlist.index(uu)]\n",
    "                    del nearHDlist[ nearHDlist.index(uu)]\n",
    "    for u in addedList:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "    HDunitList[t] += addedList\n",
    "    HDvPop[t]    = np.sum( [unitPop[u] for u in HDunitList[t] ] )\n",
    "    HDnAddedUnits[t] = len(addedList)\n",
    "    HDaddedPop[t] = np.sum( [unitPop[u] for u in addedList] )\n",
    "    if HDvPop[t] > maxDistrictPop:\n",
    "        print(\"Oops! HD\",t,\"now has overshot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after adding\",HDaddedPop[t] )\n",
    "print(\"We have addressed underpop in a total of\",len(underPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original (x) to final pop (y)\")\n",
    "plt.scatter([HDvPop[t] - HDaddedPop[t] for t in underPoppedList], [HDvPop[t] for t in underPoppedList])\n",
    "plt.axhline(y=aDP, xmin = 0.9*aDP, xmax = 1.1*aDP, ls=\"--\")\n",
    "plt.axvline(x=aDP, ymin = 0.9*aDP, ymax = 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 216,
   "id": "bc01409d-d9e4-43a6-9fae-c76aa7bdc855",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'latestAvg' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[216], line 16\u001b[0m\n\u001b[0;32m     14\u001b[0m plt\u001b[38;5;241m.\u001b[39mlegend()\n\u001b[0;32m     15\u001b[0m ampedUnitUseAvg, ampedUnitUseSD \u001b[38;5;241m=\u001b[39m getWeightedAvgAndSD(ampedUnitUse,unitPop)\n\u001b[1;32m---> 16\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mprevious unit avg and sd usage are\u001b[39m\u001b[38;5;124m\"\u001b[39m,r5(\u001b[43mlatestAvg\u001b[49m), r5(latestSD) )\n\u001b[0;32m     17\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mamped unit avg and sd usage are\u001b[39m\u001b[38;5;124m\"\u001b[39m,r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n\u001b[0;32m     18\u001b[0m plt\u001b[38;5;241m.\u001b[39mshow()\n",
      "\u001b[1;31mNameError\u001b[0m: name 'latestAvg' is not defined"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "prevUnitUse = [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in latestHDlist[t]:\n",
    "        prevUnitUse[u] += HDweight[t] * nDistricts\n",
    "\n",
    "ampedUnitUse = [0. for u in range(nUnits)]\n",
    "ampedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "ampedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in ampedHDlist[t]:\n",
    "        ampedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "plt.hist(prevUnitUse,bins=50,weights=unitPop,label=\"previous\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.legend()\n",
    "ampedUnitUseAvg, ampedUnitUseSD = getWeightedAvgAndSD(ampedUnitUse,unitPop)\n",
    "print(\"previous unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 217,
   "id": "ee512b2b-4daa-4a6b-9452-e8dfdfdebc88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "the current barredJettisonSet (usually CCB's) is {2728, 2725, 2726, 2727}\n"
     ]
    }
   ],
   "source": [
    "#CHECK ON BARRED JETTISON SET BEFORE RUNNING BELOW\n",
    "print(\"the current barredJettisonSet (usually CCB's) is\",barredJettisonSet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 218,
   "id": "dd7d9818-344c-4150-917b-57a4ee051c92",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\n",
      "Let's now square down the 1749 overPopped HDs to within 1249\n",
      "working on squaring down HD 10 time is now 0\n",
      "working on squaring down HD 65 time is now 224\n",
      "working on squaring down HD 144 time is now 1092\n",
      "working on squaring down HD 233 time is now 1411\n",
      "working on squaring down HD 291 time is now 1680\n",
      "working on squaring down HD 331 time is now 1775\n",
      "working on squaring down HD 392 time is now 1899\n",
      "working on squaring down HD 444 time is now 1974\n",
      "working on squaring down HD 481 time is now 2088\n",
      "working on squaring down HD 565 time is now 2294\n",
      "working on squaring down HD 697 time is now 2528\n",
      "working on squaring down HD 740 time is now 2760\n",
      "working on squaring down HD 783 time is now 2969\n",
      "working on squaring down HD 826 time is now 3086\n",
      "working on squaring down HD 865 time is now 3269\n",
      "working on squaring down HD 937 time is now 3733\n",
      "working on squaring down HD 1027 time is now 3958\n",
      "working on squaring down HD 1068 time is now 4050\n",
      "working on squaring down HD 1129 time is now 4109\n",
      "working on squaring down HD 1195 time is now 4466\n",
      "working on squaring down HD 1275 time is now 4542\n",
      "working on squaring down HD 1327 time is now 4588\n",
      "working on squaring down HD 1367 time is now 4649\n",
      "working on squaring down HD 1407 time is now 4661\n",
      "working on squaring down HD 1450 time is now 4683\n",
      "working on squaring down HD 1543 time is now 4725\n",
      "working on squaring down HD 1604 time is now 4838\n",
      "working on squaring down HD 1655 time is now 5149\n",
      "working on squaring down HD 1687 time is now 5221\n",
      "working on squaring down HD 1723 time is now 5305\n",
      "working on squaring down HD 1779 time is now 5416\n",
      "working on squaring down HD 1815 time is now 5498\n",
      "working on squaring down HD 1847 time is now 5594\n",
      "working on squaring down HD 1885 time is now 5712\n",
      "working on squaring down HD 2054 time is now 5863\n",
      "working on squaring down HD 2107 time is now 5980\n",
      "working on squaring down HD 2198 time is now 6131\n",
      "working on squaring down HD 2264 time is now 6235\n",
      "working on squaring down HD 2308 time is now 6405\n",
      "working on squaring down HD 2371 time is now 6475\n",
      "working on squaring down HD 2416 time is now 6604\n",
      "working on squaring down HD 2473 time is now 6718\n",
      "working on squaring down HD 2533 time is now 6748\n",
      "working on squaring down HD 2575 time is now 6782\n",
      "working on squaring down HD 2629 time is now 6805\n",
      "working on squaring down HD 2729 time is now 6816\n",
      "working on squaring down HD 2830 time is now 6832\n",
      "working on squaring down HD 2871 time is now 6853\n",
      "working on squaring down HD 2947 time is now 6883\n",
      "working on squaring down HD 3179 time is now 6942\n",
      "working on squaring down HD 3231 time is now 7110\n",
      "working on squaring down HD 3661 time is now 7134\n",
      "working on squaring down HD 3712 time is now 7164\n",
      "working on squaring down HD 3833 time is now 7223\n",
      "working on squaring down HD 3912 time is now 7370\n",
      "working on squaring down HD 3947 time is now 7701\n",
      "working on squaring down HD 3984 time is now 7853\n",
      "working on squaring down HD 4020 time is now 7945\n",
      "working on squaring down HD 4095 time is now 7976\n",
      "We have addressed overpop in a total of 1749 HDs\n",
      "Here is a scatterplot of original to final pop\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#SQUARING DOWN\n",
    "print(\"Continuing with narrowing the distro.  This loop: remove overused units from overpopped HDs\")\n",
    "#HDunitList = [ampedHDlist[t].copy() for t in range(nHDs)]\n",
    "#HDvPop =     [ampedHDpop[t]         for t in range(nHDs)]\n",
    "#unitUse =    [ampedUnitUse[u]       for u in range(nUnits)] #saving in case I need to re-run\n",
    "HDnShedUnits = [0]*nHDs\n",
    "overPoppedList = list()\n",
    "startTime = time.time()\n",
    "for t,pop in enumerate(HDvPop):\n",
    "    if pop > maxDistrictPop and t in popHDlist:\n",
    "        overPoppedList.append(t)\n",
    "\n",
    "maxGap = 0.9 * np.median(unitPop)   \n",
    "print(\"Let's now square down the\",len(overPoppedList),\"overPopped HDs to within\", int(maxGap))   \n",
    "for ii,t in enumerate(overPoppedList):\n",
    "    if ii%30 == 0:\n",
    "        print(\"working on squaring down HD\",t,\"time is now\",int(time.time()-startTime))\n",
    "    unbroken, noEnclave, sPL, ePL = enclaveCheck(HDunitList[t],unitNbrs)\n",
    "    if not (unbroken and noEnclave):\n",
    "        print(\"SKIPPING shedding attempt on overpopped HD\",t,\"with pop\",HDvPop[t],\"because it was not legal to start\")\n",
    "    else:\n",
    "        #avgDist = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        excess = HDvPop[t] - aDP\n",
    "        origExcess = excess\n",
    "        HDboundaryList, HDboundaryScore = list(), list()  #these will be dynamic lists of the overused border units to jettison\n",
    "        distList = [hdCP[t].distance(unitCP[u]) for u in HDunitList[t] ]\n",
    "        starterU = HDunitList[t][distList.index(np.min(distList))]\n",
    "        barredSet = barredJettisonSet  #new 4/10/24 for MN, ban CCB jettisoning from ALL HD's, not just near ones\n",
    "        #barredSet = set(get2nbrs([starterU],unitNbrs)).union(barredJettisonSet)  #weaker specification - must be close to be barred\n",
    "\n",
    "        for u in set(HDunitList[t]).difference(barredSet):\n",
    "            isBoundary = False\n",
    "            for uu in unitNbrs[u]:\n",
    "                if uu not in HDunitList[t]:\n",
    "                    isBoundary = True\n",
    "                    break\n",
    "            if isBoundary and HDvPop[t] - unitPop[u] > aDP - maxGap:  #shedding this unit won't send us too far under targetpop\n",
    "                HDboundaryList.append(u)\n",
    "                HDboundaryScore.append((1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t])  #low-score = bias toward far, overused\n",
    "        currList = HDunitList[t].copy()\n",
    "        shedList, stillGoing = list(), True\n",
    "        while excess > maxGap and len(HDboundaryList) > 0 and stillGoing:   #shed the highest-scoring neighboring overused unit until we've roughly squared the HDpop\n",
    "            idx, i, notYetPicked = np.argsort(HDboundaryScore), 0, True\n",
    "            while i < len(HDboundaryScore) and notYetPicked and stillGoing:        \n",
    "                listNo = idx[i]   #low (large negative) score is preferred to shed\n",
    "                unitNoToShed = HDboundaryList[listNo]  # attempt to shed this unit ...\n",
    "                tryList = list(set(currList).difference( {unitNoToShed} ) )\n",
    "                unbroken, noEnclave, sPL, ePL = enclaveCheck(tryList,unitNbrs) \n",
    "                if unbroken and noEnclave:             #... if that won't eff up contiguity\n",
    "                    notYetPicked = False\n",
    "                else:\n",
    "                    i +=1\n",
    "            if notYetPicked:\n",
    "                stillGoing = False  #can't drop any more units without creating an enclave\n",
    "                print(\"can't drop any more units to HD\",t,\"without creating an enclave\")\n",
    "            else: #add this eligible unit\n",
    "                shedList.append(unitNoToShed)\n",
    "                excess -= unitPop[unitNoToShed]        \n",
    "                del currList[currList.index(unitNoToShed) ]\n",
    "                del HDboundaryList[listNo]\n",
    "                del HDboundaryScore[listNo]\n",
    "                for u in unitNbrs[unitNoToShed]:      # ... and ID any neighboring units that will now be on boundary after we shed this unit\n",
    "                    if u in currList and u not in HDboundaryList and (unitPop[u] <= excess + maxGap and\n",
    "                                                                      u not in barredSet): \n",
    "                        HDboundaryList.append(u)\n",
    "                        HDboundaryScore.append( (1. - unitUse[u]) - unitCP[u].distance(hdCP[t]) / avgDist[t] )  #low-score, bias toward far & overused       \n",
    "                for uu in HDboundaryList.copy():\n",
    "                    if unitPop[uu] > excess + maxGap:  #checking to see if the latest pop change DQ's any large units on current boundary\n",
    "                        del HDboundaryScore[HDboundaryList.index(uu)]\n",
    "                        del HDboundaryList[HDboundaryList.index(uu)]   \n",
    "        for u in shedList:\n",
    "            unitUse[u] -= HDweight[t] * nDistricts\n",
    "        HDunitList[t], HDvPop[t] = currList.copy(), np.sum( [unitPop[u] for u in currList ] )    \n",
    "        if HDvPop[t] < minDistrictPop:\n",
    "            print(\"Oops! HD\",t,\"now has undershot pop =\",int(HDvPop[t]),\"not\",int(aDP),\"after shedding\",\n",
    "                 np.sum([unitPop[u] for u in shedList]) )\n",
    "\n",
    "        HDnShedUnits[t] = -1 * len(shedList)\n",
    "\n",
    "print(\"We have addressed overpop in a total of\",len(overPoppedList),\"HDs\")\n",
    "print(\"Here is a scatterplot of original to final pop\")\n",
    "plt.scatter([ampedHDpop[t] for t in overPoppedList], [HDvPop[t] for t in overPoppedList])\n",
    "plt.axhline(aDP, 0.9*aDP, 1.1*aDP, ls=\"--\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "id": "9a19b23e-43cc-4609-9ee7-6d1057a7a9e1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here are the stats prior to any equi-pop patching\n",
      "amped unit avg and sd usage are 1.02898 0.12643\n",
      "shed unit avg and sd usage are 1.00204 0.10232\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "and here are the final populations\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 4110\n",
      "working on HD 300 out of 4110\n",
      "working on HD 601 out of 4110\n",
      "working on HD 901 out of 4110\n",
      "working on HD 1201 out of 4110\n",
      "working on HD 1501 out of 4110\n",
      "working on HD 1802 out of 4110\n",
      "working on HD 2103 out of 4110\n",
      "working on HD 2403 out of 4110\n",
      "working on HD 2703 out of 4110\n",
      "working on HD 3003 out of 4110\n",
      "working on HD 3303 out of 4110\n",
      "working on HD 3603 out of 4110\n",
      "working on HD 3903 out of 4110\n",
      "all done checking HD and complement contiguity for all 4110 HDs\n",
      "underpop contigFail, enclaveFail = 0 0 out of 558\n",
      "overpop contigFail, enclaveFail = 0 0 out of 1749\n",
      "total contigFail, enclaveFail =  0 0\n",
      "CCB unit 2725 with pop 314005.0 now has use 0.95959\n",
      "CCB unit 2726 with pop 148064.0 now has use 0.98491\n",
      "CCB unit 2727 with pop 216736.0 now has use 0.96349\n",
      "CCB unit 2728 with pop 65226.0 now has use 1.00025\n"
     ]
    }
   ],
   "source": [
    "print(\"Here are the stats prior to any equi-pop patching\")\n",
    "shedUnitUse = [0. for u in range(nUnits)]\n",
    "shedHDlist = [HDunitList[t].copy() for t in range(nHDs)]\n",
    "shedHDpop = [HDvPop[t] for t in range(nHDs) ]\n",
    "for t in popHDlist:\n",
    "    for u in shedHDlist[t]:\n",
    "        shedUnitUse[u] += HDweight[t] * nDistricts   #KISS - recalc these\n",
    "#plt.hist(latestUnitUse,bins=50,weights=unitPop,label=\"pre-squaring\",histtype=\"step\")\n",
    "plt.hist(ampedUnitUse, bins=50, weights=unitPop,label=\"amped\",histtype=\"step\")\n",
    "plt.hist(shedUnitUse, bins=50, weights=unitPop,label=\"shed\",histtype=\"step\")\n",
    "plt.legend()\n",
    "#latestAvg, latestSD = getWeightedAvgAndSD(latestUnitUse,unitPop)\n",
    "shedUnitUseAvg, shedUnitUseSD = getWeightedAvgAndSD(shedUnitUse,unitPop)\n",
    "#print(\"orig unit avg and sd usage are\",r5(latestAvg), r5(latestSD) )\n",
    "print(\"amped unit avg and sd usage are\",r5(ampedUnitUseAvg), r5(ampedUnitUseSD) )\n",
    "print(\"shed unit avg and sd usage are\", r5(shedUnitUseAvg),  r5(shedUnitUseSD) )\n",
    "plt.show()\n",
    "# note: when I ran this early Jan, went from 0.12662 to 0.09961 to 0.09432 SD orig-amped-shed, but contig not yet done\n",
    "print(\"and here are the final populations\")\n",
    "plt.hist([shedHDpop[t] for t in popHDlist],bins=20)\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "failEnclaveSet, failContigSet = set(), set()\n",
    "for i,t in enumerate(popHDlist):\n",
    "    if i%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs,5)\n",
    "    if not noEnclave:\n",
    "        noEnclave, eList = isContiguous(list({u for u in range(nUnits)}.difference(set(HDunitList[t]))),unitNbrs)\n",
    "    if not unbroken or not noEnclave:\n",
    "        #print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "        pass\n",
    "    if not unbroken:\n",
    "        failContigSet.add(t)\n",
    "    if not noEnclave:\n",
    "        failEnclaveSet.add(t)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")\n",
    "failContigUnderpopped, failEnclaveUnderpopped = set(underPoppedList).intersection(failContigSet), set(underPoppedList).intersection(failEnclaveSet)\n",
    "failContigOverpopped, failEnclaveOverpopped = set(overPoppedList).intersection(failContigSet), set(overPoppedList).intersection(failEnclaveSet)\n",
    "print(\"underpop contigFail, enclaveFail =\",len(failContigUnderpopped), len(failEnclaveUnderpopped),\"out of\",len(underPoppedList))\n",
    "print(\"overpop contigFail, enclaveFail =\",len(failContigOverpopped), len(failEnclaveOverpopped),\"out of\",len(overPoppedList))\n",
    "print(\"total contigFail, enclaveFail = \",len(failContigSet), len(failEnclaveSet) )\n",
    "for u in range(nUnits):\n",
    "    if abs( allUnits[u]%1 - 0.25) < 0.01:\n",
    "        print(\"CCB unit\",u,\"with pop\",unitPop[u],\"now has use\",r5(unitUse[u]) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "id": "af4a9d26-98ab-4ceb-96c1-f2083abcc5d7",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will remove CCB unit 1647 from HD 962 leaving it with pop 740526.0\n",
      "we will remove CCB unit 1647 from HD 1321 leaving it with pop 715813.0\n",
      "we will remove CCB unit 1648 from HD 1481 leaving it with pop 426197.66490213\n",
      "we will remove CCB unit 1647 from HD 1999 leaving it with pop 738985.0\n"
     ]
    }
   ],
   "source": [
    "#see MD code if we need to remove a stuck CCB's from any HDs and then redo the square-up after dropping them\n",
    "                \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "id": "e7bfa674-8fc8-42c8-86e9-76d334d3c47c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"unpatchedOpt3redoContigGoodPop.csv\" #\"contigUnpatchedB.csv\" unpatchedContigGoodPop.csv\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 430,
   "id": "c0c3a3d8-cf79-40ad-aa2e-b6793266f1d4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "prior to patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    }
   ],
   "source": [
    "#SKIP THIS FOR STATES WITH FRAGMENTED VTD'S ###########\n",
    "print(\"prior to patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist = [list() for u in range(nUnits)]\n",
    "for u in range(nUnits):\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        unitVTDlist[u] = [allUnits[u]]\n",
    "        for i,uu in enumerate(surrounders):\n",
    "            if u == uu:\n",
    "                unitVTDlist[u].append(surroundedVTDs[i])\n",
    "\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        vtdList[t] += unitVTDlist[u]\n",
    "    #add more stuff here to convert to vtd lists\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"needsEnclaveRemoval.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "7a36c0ba-5a68-445b-a223-b7fa55dfd728",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are 4110 HD centers\n"
     ]
    }
   ],
   "source": [
    "nHDs = len(vtdGeom)\n",
    "print(\"there are\",nHDs,\"HD centers\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "1b794580-5a58-4238-b310-7c87872ed679",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\n",
      "Must have already established unitGeoms, pops, topology -- or read in via next block\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./2024state_HD_output/MN4110unpatchedContigGoodPop.csv ./2024state_HD_output/MN4110unpatchedOpt3redoContigGoodPop.csv\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sum of HDweight should be unity, actually is 0.9999999999999076\n",
      "I will now renormalize\n",
      "normalized weight is now 1.0\n",
      "I read in 4110 HD lists of units\n",
      "orig unit avg and sd usage are 1.00204 0.10232\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"this optional RESTART block pulls in an existing UNIT (not vtd) list for patching\") #vtdlist for patching\")\n",
    "print(\"Must have already established unitGeoms, pops, topology -- or read in via next block\")\n",
    "guessedFile = \"enter the unpatched UNIT list file, e.g. ./2024state_HD_output/\"+STATE+str(nHDs)+\"unpatchedContigGoodPop.csv\"\n",
    "infile = input(guessedFile)\n",
    "inDF = pd.read_csv(infile)\n",
    "vtdListString = inDF[\"HDunitList\"]  #inDF[\"HDvtdList\"]\n",
    "nHDs = len(vtdListString)\n",
    "inVTDlist = [ast.literal_eval(vtdListString[t]) for t in range(nHDs)]\n",
    "HDweight = inDF[\"HDweight\"]\n",
    "sumWt = np.sum(HDweight)\n",
    "print(\"sum of HDweight should be unity, actually is\",sumWt)\n",
    "print(\"I will now renormalize\")\n",
    "HDweight = [HDweight[t] /sumWt for t in range(nHDs)]\n",
    "print(\"normalized weight is now\",np.sum(HDweight))\n",
    "HDvPop = inDF[\"HDvPop\"].to_list()\n",
    "hdCPx, hdCPy = inDF[\"centroid x\"], inDF[\"centroid y\"]\n",
    "hdCP = [Point(hdCPx[t], hdCPy[t]) for t in range(nHDs)]\n",
    "print(\"I read in\",nHDs,\"HD lists of units\") #vtds\")\n",
    "HDunitList = [inVTDlist[t].copy() for t in range(nHDs)]\n",
    "#HDunitList = [list() for t in range(nHDs)]\n",
    "#for t in range(nHDs):\n",
    "#    if t%500 == 0:\n",
    "#        print(\"working on converting HD\",t,\"from vtd list to unit list\")\n",
    "#    for v in inVTDlist[t]:  #this will skip over surrounded units, whose pops we have added to their surrounders\n",
    "#        if v in allUnits:\n",
    "#            HDunitList[t].append(allUnits.index(v))\n",
    "#    for c in unitCounties:\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(c+0.5)\n",
    "#            HDunitList[t].append(u)\n",
    "#    for j, L in enumerate(CCBlist):\n",
    "#        c = L[0]\n",
    "#        if countyTractList[c][0] in inVTDlist[t]:\n",
    "#            u = allUnits.index(j+0.25)\n",
    "#            HDunitList[t].append(u) \n",
    "            \n",
    "unitUse = [0. for u in range(nUnits)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        unitUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(unitUse, bins=50, weights=unitPop,label=\"read-in\",histtype=\"step\")\n",
    "plt.legend()\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "print(\"orig unit avg and sd usage are\",r5(unpatchedAvg), r5(unpatchedSD) )\n",
    "plt.show()\n",
    "currAvg, currSD = unpatchedAvg, unpatchedSD"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 176,
   "id": "8014f0bf-74bb-40bc-b217-af4e204ea9a7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "upon restart, need to pull in unit topology and data\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv ./state_map_files/MNunitTopologies_06Apr24.csv\n"
     ]
    }
   ],
   "source": [
    "print(\"upon restart, need to pull in unit topology and data\")  #note, this won't have geometries for plotting, but fine for patching\n",
    "topologyFile = \"enter the unpatched UNIT list file, e.g. ./state_map_files/MNunitTopologies_06Apr24.csv\"\n",
    "infile = input(topologyFile)\n",
    "topDF = pd.read_csv(infile)\n",
    "unitCPx, unitCPy, unitPop = topDF[\"centroid x\"], topDF[\"centroid y\"], topDF[\"unitPop\"]\n",
    "nUnits = len(unitPop)\n",
    "unitCP = [Point(unitCPx[u], unitCPy[u]) for u in range(nUnits) ]\n",
    "onBorder = topDF[\"onBorder\"]\n",
    "borderSet = set()\n",
    "for i, onB in enumerate(onBorder):\n",
    "    if onB == 1:\n",
    "        borderSet.add(i)\n",
    "borderList = list(borderSet)\n",
    "\n",
    "nbrListString = topDF[\"neighborList\"]\n",
    "unitNbrs = [ast.literal_eval(nbrListString[u]) for u in range(nUnits)]\n",
    "unitParentVTDno = topDF[\"unitParentVTDno\"]  #NOTE: some units are VTD fragments, so they share a parentVTDno\n",
    "uVLstring = topDF[\"unitVTDlist\"]\n",
    "unitNbrs = [ast.literal_eval(uVLstring[u]) for u in range(nUnits)]\n",
    "allUnits = topDF[\"allUnits\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "5f3a5392-11f1-4061-a458-aecd834b2748",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working avg precinct-to-HDcP distance for HD 0\n",
      "working avg precinct-to-HDcP distance for HD 800\n",
      "working avg precinct-to-HDcP distance for HD 1600\n",
      "working avg precinct-to-HDcP distance for HD 2400\n",
      "working avg precinct-to-HDcP distance for HD 3200\n",
      "working avg precinct-to-HDcP distance for HD 4000\n",
      "all avgDist to HD centers computed\n"
     ]
    }
   ],
   "source": [
    "#needed for restart only  about 5sec per 2000 HDs\n",
    "avgDist = [0. for t in range(nHDs)]\n",
    "popHDlist = list()\n",
    "for t in range(nHDs):\n",
    "    if t%800 == 0:\n",
    "        print(\"working avg precinct-to-HDcP distance for HD\",t)\n",
    "    if HDvPop[t] > 0.1 * aDP:\n",
    "        avgDist[t] = np.sum([unitPop[u]*unitCP[u].distance(hdCP[t]) for u in HDunitList[t] ]) / HDvPop[t]\n",
    "        popHDlist.append(t)\n",
    "print(\"all avgDist to HD centers computed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "ea0db02f-9df8-4906-acb4-086c29c0fcc1",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking for discontiguities for HD 0\n",
      "checking for discontiguities for HD 500\n",
      "checking for discontiguities for HD 1000\n",
      "checking for discontiguities for HD 1500\n",
      "checking for discontiguities for HD 2000\n",
      "checking for discontiguities for HD 2500\n",
      "checking for discontiguities for HD 3000\n",
      "checking for discontiguities for HD 3500\n",
      "checking for discontiguities for HD 4000\n",
      "out of 4106 total HDs, there were 4106 0 0 0 HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\n"
     ]
    }
   ],
   "source": [
    "discontigOnly, enclaveOnly, bothProblems, cleanList = list(), list(), list(), list()  #optional contiguity check\n",
    "for t in popHDlist:\n",
    "    if t%500 == 0:\n",
    "        print(\"checking for discontiguities for HD\",t)\n",
    "    unbroken, noEnclave,smallPieceList,enclaveList = enclaveCheck(HDunitList[t], unitNbrs)\n",
    "    if unbroken and noEnclave:\n",
    "        cleanList.append(t)\n",
    "    if unbroken and not noEnclave:\n",
    "        enclaveOnly.append(t)\n",
    "    if not unbroken and noEnclave:\n",
    "        discontigOnly.append(t)\n",
    "    if not unbroken and not noEnclave:\n",
    "        bothProblems.append(t)\n",
    "print(\"out of\",len(popHDlist),\"total HDs, there were\",len(cleanList),len(discontigOnly),len(enclaveOnly),\n",
    "      len(bothProblems),\"HDs that were clean, discontig only, enclave-only, both problems.  Should all be zeroes\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "27b42f93-dc87-4afe-8eb3-f30fdff4a737",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking unitUse, pop for county clusters\n",
      "2725 0.95959 314005.0\n",
      "2726 0.98491 148064.0\n",
      "2727 0.96349 216736.0\n",
      "2728 1.00025 65226.0\n"
     ]
    }
   ],
   "source": [
    "print(\"checking unitUse, pop for county clusters\")\n",
    "for uNo in allUnits:\n",
    "    if uNo - int(uNo) > 0.23 and uNo - int(uNo) < 0.27:\n",
    "        u = allUnits.index(uNo)\n",
    "        print(u,r5(unitUse[u]), unitPop[u])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "72941b8f-7be6-4a31-9377-618f44a34336",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unpatchedUnitUse = unitUse.copy()              #... for safekeeping\n",
    "unpatchedHDlist =  [HDunitList[t].copy() for t in range(nHDs) ]\n",
    "unpatchedHDpop =   HDvPop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "5f9ca091-1eb6-4135-a233-7f5ae0f5e3d1",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "unitUse = unpatchedUnitUse.copy()              #... for restarting\n",
    "HDunitList =  [unpatchedHDlist[t].copy() for t in range(nHDs) ]\n",
    "HDvPop =   unpatchedHDpop.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "e9dd457d-fb37-49cf-9b19-19c17c328ede",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.07\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.07\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will stop patching on individual underused units when their usage exceeds 0.93\n",
      "this would currently cover a total of 602 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 300\n",
      "enter updated stopMinUse value for ending usage boost on a unit 0.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 962 units out of 2729 with usage below 0.97\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency 15\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 35665\n",
      "current avg and SD of unit usage are 1.00204 0.10232 . Now trying to increase up to 300 units' underusage\n",
      "all done trying to increase usage of unit 575 final usage = 0.97143 3395 sec elapsed 362 1 successful, failed patches, couldn't start= 98\n",
      "current avg and SD of usage are 1.00205 0.09827\n",
      "all done trying to increase usage of unit 2622 final usage = 0.9704 6603 sec elapsed 298 0 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 1.00205 0.09471\n",
      "all done trying to increase usage of unit 591 final usage = 0.87676 9316 sec elapsed 276 0 successful, failed patches, couldn't start= 56\n",
      "current avg and SD of usage are 1.00205 0.09359\n",
      "all done trying to increase usage of unit 623 final usage = 0.67178 9375 sec elapsed 8 0 successful, failed patches, couldn't start= 52\n",
      "current avg and SD of usage are 1.00205 0.09357\n",
      "all done trying to increase usage of unit 601 final usage = 0.69833 9855 sec elapsed 55 0 successful, failed patches, couldn't start= 18\n",
      "current avg and SD of usage are 1.00205 0.09332\n",
      "all done trying to increase usage of unit 2356 final usage = 0.97378 9882 sec elapsed 70 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00186 0.09046\n",
      "all done trying to increase usage of unit 597 final usage = 0.83982 12730 sec elapsed 221 0 successful, failed patches, couldn't start= 60\n",
      "current avg and SD of usage are 1.00186 0.08987\n",
      "all done trying to increase usage of unit 2421 final usage = 0.71869 13202 sec elapsed 57 2 successful, failed patches, couldn't start= 279\n",
      "current avg and SD of usage are 1.00185 0.08912\n",
      "all done trying to increase usage of unit 611 final usage = 0.68428 13335 sec elapsed 12 0 successful, failed patches, couldn't start= 50\n",
      "current avg and SD of usage are 1.00185 0.08908\n",
      "all done trying to increase usage of unit 612 final usage = 0.68429 13422 sec elapsed 5 0 successful, failed patches, couldn't start= 51\n",
      "current avg and SD of usage are 1.00185 0.08906\n",
      "all done trying to increase usage of unit 609 final usage = 0.70196 13798 sec elapsed 26 0 successful, failed patches, couldn't start= 295\n",
      "current avg and SD of usage are 1.00185 0.08889\n",
      "all done trying to increase usage of unit 602 final usage = 0.698 14320 sec elapsed 43 0 successful, failed patches, couldn't start= 40\n",
      "current avg and SD of usage are 1.00185 0.08877\n",
      "all done trying to increase usage of unit 606 final usage = 0.71848 15263 sec elapsed 69 0 successful, failed patches, couldn't start= 214\n",
      "current avg and SD of usage are 1.00185 0.08874\n",
      "all done trying to increase usage of unit 607 final usage = 0.71848 16299 sec elapsed 69 0 successful, failed patches, couldn't start= 214\n",
      "current avg and SD of usage are 1.00185 0.08867\n",
      "starting to increase usage for unit 584 with usage 0.68537 . Total UU units tried = 15\n",
      "all done trying to increase usage of unit 584 final usage = 0.83782 18134 sec elapsed 195 0 successful, failed patches, couldn't start= 280\n",
      "current avg and SD of usage are 1.00184 0.0865\n",
      "all done trying to increase usage of unit 610 final usage = 0.82391 20850 sec elapsed 198 0 successful, failed patches, couldn't start= 2\n",
      "current avg and SD of usage are 1.00184 0.08577\n",
      "all done trying to increase usage of unit 2431 final usage = 0.91326 21591 sec elapsed 159 2 successful, failed patches, couldn't start= 36\n",
      "current avg and SD of usage are 1.00183 0.08148\n",
      "all done trying to increase usage of unit 2617 final usage = 0.97096 23849 sec elapsed 216 3 successful, failed patches, couldn't start= 12\n",
      "current avg and SD of usage are 1.00183 0.08084\n",
      "all done trying to increase usage of unit 2430 final usage = 0.97002 26757 sec elapsed 292 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00185 0.07778\n",
      "all done trying to increase usage of unit 2427 final usage = 0.83374 29026 sec elapsed 126 0 successful, failed patches, couldn't start= 132\n",
      "current avg and SD of usage are 1.00185 0.07696\n",
      "all done trying to increase usage of unit 595 final usage = 0.7481 30167 sec elapsed 90 0 successful, failed patches, couldn't start= 163\n",
      "current avg and SD of usage are 1.00185 0.07611\n",
      "all done trying to increase usage of unit 620 final usage = 0.97245 35179 sec elapsed 289 0 successful, failed patches, couldn't start= 39\n",
      "current avg and SD of usage are 1.00184 0.07549\n",
      "all done trying to increase usage of unit 2621 final usage = 0.97056 43975 sec elapsed 219 1 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 1.00184 0.07473\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[39], line 99\u001b[0m\n\u001b[0;32m     97\u001b[0m listNo \u001b[38;5;241m=\u001b[39m idx[ij]   \u001b[38;5;66;03m#work from low to high score\u001b[39;00m\n\u001b[0;32m     98\u001b[0m addU \u001b[38;5;241m=\u001b[39m addCandidates[listNo]\n\u001b[1;32m---> 99\u001b[0m contig,cContig, __, ___ \u001b[38;5;241m=\u001b[39m \u001b[43menclaveCheck\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mlist\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mtrySet\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43munion\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[43maddU\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43munitNbrs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    100\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m contig \u001b[38;5;129;01mand\u001b[39;00m cContig:\n\u001b[0;32m    101\u001b[0m     notYetPicked \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n",
      "Cell \u001b[1;32mIn[2], line 734\u001b[0m, in \u001b[0;36menclaveCheck\u001b[1;34m(UNITLIST, UNITNBRS, maxLoops)\u001b[0m\n\u001b[0;32m    732\u001b[0m         newSet \u001b[38;5;241m=\u001b[39m newSet\u001b[38;5;241m.\u001b[39munion( \u001b[38;5;28mset\u001b[39m(UNITNBRS[UU])\u001b[38;5;241m.\u001b[39mdifference(UNITSET) )\n\u001b[0;32m    733\u001b[0m     ADJLIST \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(newSet)\n\u001b[1;32m--> 734\u001b[0m     noEnclave, enclaveList \u001b[38;5;241m=\u001b[39m   \u001b[43misContiguous\u001b[49m\u001b[43m(\u001b[49m\u001b[43mADJLIST\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mUNITNBRS\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m    735\u001b[0m \u001b[38;5;66;03m#isJiggy = noEnclave and unbroken\u001b[39;00m\n\u001b[0;32m    736\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m unbroken, noEnclave, smallPieceList, enclaveList\n",
      "Cell \u001b[1;32mIn[2], line -1\u001b[0m, in \u001b[0;36misContiguous\u001b[1;34m(VLIST, NEIGHBORLIST, returnBiggestPiece)\u001b[0m\n\u001b[0;32m      0\u001b[0m <Error retrieving source code with stack_data see ipython/ipython#13598>\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#FIRST PATCHING BLOCK - boosting underuse.  Suppresses long strings.  For some states (e.g. MA), do overpopped first. MA:over-und-over-und\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used\")\n",
    "maxSD = 0.07  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs, startTime = list(), time.time()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"begin usage increase for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Sec, total UU units tried =\",\n",
    "              int(time.time()-startTime),len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    idx0 = np.argsort(uuuDists)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs): #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to increase usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e2377b41-61df-4f0d-9d87-a0557362328d",
   "metadata": {},
   "outputs": [],
   "source": [
    ".99959 0.09151  8:44 0.08996"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "861f29d3-b727-49af-90a8-aa9a963e0741",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00204 1.00184 and their SDs are 0.10232 0.0745\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 4110\n",
      "working on HD 300 out of 4110\n",
      "working on HD 600 out of 4110\n",
      "working on HD 900 out of 4110\n",
      "working on HD 1200 out of 4110\n",
      "working on HD 1500 out of 4110\n",
      "working on HD 1800 out of 4110\n",
      "working on HD 2100 out of 4110\n",
      "working on HD 2400 out of 4110\n",
      "working on HD 2700 out of 4110\n",
      "working on HD 3000 out of 4110\n",
      "working on HD 3300 out of 4110\n",
      "working on HD 3600 out of 4110\n",
      "working on HD 3900 out of 4110\n",
      "all done checking HD and complement contiguity for all 4110 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "1ee72cf0-618e-411f-aa37-518ac2c679ce",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "#optional intermediate save\n",
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"underPatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "77c07848-50c2-4fe9-8841-768b02bf4ac4",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "default use threshold for moving on to next overused unit is 1.08\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated stopMaxUse value 1.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 691 units out of 2729 with usage above 1.03\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.05\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "this block reduces overuse, with exchanges up to 35665\n",
      "current avg and SD of unit usage are 1.00184 0.0745 . Now trying to reduce up to 691 units' overusage\n",
      "starting to reduce usage for unit 1279 with usage 1.35841 . Total units tried = 1\n",
      "try to drop unit 1279 from 37 th HD.  usage down to 1.2975420634806538\n",
      "try to drop unit 1279 from 74 th HD.  usage down to 1.2498139838576803\n",
      "try to drop unit 1279 from 111 th HD.  usage down to 1.226986657657039\n",
      "try to drop unit 1279 from 148 th HD.  usage down to 1.2008550258705173\n",
      "try to drop unit 1279 from 185 th HD.  usage down to 1.167458688294417\n",
      "all done trying to reduce usage of unit 1279 final usage = 1.16458 155 sec elapsed 112 2 successful, failed patches, couldn't start= 74\n",
      "current avg and SD of usage are 1.00181 0.06919\n",
      "starting to reduce usage for unit 677 with usage 1.33008 . Total units tried = 2\n",
      "try to drop unit 677 from 49 th HD.  usage down to 1.3265125662096455\n",
      "try to drop unit 677 from 98 th HD.  usage down to 1.3262644278605997\n",
      "try to drop unit 677 from 147 th HD.  usage down to 1.3262644278605997\n",
      "try to drop unit 677 from 196 th HD.  usage down to 1.3082975290957874\n",
      "try to drop unit 677 from 245 th HD.  usage down to 1.2675972322059632\n",
      "all done trying to reduce usage of unit 677 final usage = 1.26573 1598 sec elapsed 65 2 successful, failed patches, couldn't start= 183\n",
      "current avg and SD of usage are 1.0018 0.06813\n",
      "starting to reduce usage for unit 1286 with usage 1.28535 . Total units tried = 3\n",
      "try to drop unit 1286 from 24 th HD.  usage down to 1.280892961597774\n",
      "try to drop unit 1286 from 48 th HD.  usage down to 1.2581721806769484\n",
      "try to drop unit 1286 from 72 th HD.  usage down to 1.2404856642274442\n",
      "try to drop unit 1286 from 96 th HD.  usage down to 1.2273539584900854\n",
      "try to drop unit 1286 from 120 th HD.  usage down to 1.2024125496320375\n",
      "all done trying to reduce usage of unit 1286 final usage = 1.18993 1723 sec elapsed 62 2 successful, failed patches, couldn't start= 59\n",
      "current avg and SD of usage are 1.00179 0.0662\n",
      "starting to reduce usage for unit 267 with usage 1.26427 . Total units tried = 4\n",
      "try to drop unit 267 from 71 th HD.  usage down to 1.2056481615506431\n",
      "try to drop unit 267 from 142 th HD.  usage down to 1.157364924943371\n",
      "try to drop unit 267 from 213 th HD.  usage down to 1.125634058320186\n",
      "try to drop unit 267 from 284 th HD.  usage down to 1.0755493653370702\n",
      "try to drop unit 267 from 355 th HD.  usage down to 1.0496981158658536\n",
      "all done trying to reduce usage of unit 267 final usage = 1.04934 4477 sec elapsed 293 45 successful, failed patches, couldn't start= 18\n",
      "current avg and SD of usage are 1.00177 0.06395\n",
      "starting to reduce usage for unit 1436 with usage 1.24252 . Total units tried = 5\n",
      "try to drop unit 1436 from 37 th HD.  usage down to 1.1360614766264496\n",
      "try to drop unit 1436 from 74 th HD.  usage down to 1.049599982055526\n",
      "all done trying to reduce usage of unit 1436 final usage = 1.0294 4513 sec elapsed 61 0 successful, failed patches, couldn't start= 28\n",
      "current avg and SD of usage are 1.00177 0.0598\n",
      "starting to reduce usage for unit 706 with usage 1.26573 . Total units tried = 6\n",
      "try to drop unit 706 from 31 th HD.  usage down to 1.2408137115363524\n",
      "try to drop unit 706 from 62 th HD.  usage down to 1.1770477634778802\n",
      "try to drop unit 706 from 93 th HD.  usage down to 1.1369853363553795\n",
      "try to drop unit 706 from 124 th HD.  usage down to 1.1102018156857698\n",
      "try to drop unit 706 from 155 th HD.  usage down to 1.0916222815620156\n",
      "all done trying to reduce usage of unit 706 final usage = 1.09104 4969 sec elapsed 90 3 successful, failed patches, couldn't start= 62\n",
      "current avg and SD of usage are 1.00177 0.05656\n",
      "starting to reduce usage for unit 476 with usage 1.23528 . Total units tried = 7\n",
      "try to drop unit 476 from 59 th HD.  usage down to 1.1597762128550053\n",
      "try to drop unit 476 from 118 th HD.  usage down to 1.1224040540478646\n",
      "try to drop unit 476 from 177 th HD.  usage down to 1.0858646307171833\n",
      "try to drop unit 476 from 236 th HD.  usage down to 1.0718917780339072\n",
      "try to drop unit 476 from 295 th HD.  usage down to 1.0320957141109466\n",
      "all done trying to reduce usage of unit 476 final usage = 1.03199 7920 sec elapsed 218 23 successful, failed patches, couldn't start= 55\n",
      "current avg and SD of usage are 1.00177 0.0545\n",
      "starting to reduce usage for unit 58 with usage 1.23407 . Total units tried = 8\n",
      "try to drop unit 58 from 35 th HD.  usage down to 1.1526264638147306\n",
      "try to drop unit 58 from 70 th HD.  usage down to 1.033472391279124\n",
      "all done trying to reduce usage of unit 58 final usage = 1.02282 8245 sec elapsed 58 1 successful, failed patches, couldn't start= 11\n",
      "current avg and SD of usage are 1.00171 0.05295\n",
      "starting to reduce usage for unit 2545 with usage 1.19411 . Total units tried = 9\n",
      "try to drop unit 2545 from 33 th HD.  usage down to 1.1138678144584018\n",
      "try to drop unit 2545 from 66 th HD.  usage down to 1.0695337627622115\n",
      "all done trying to reduce usage of unit 2545 final usage = 1.02724 8289 sec elapsed 47 0 successful, failed patches, couldn't start= 45\n",
      "current avg and SD of usage are 1.00168 0.04973\n",
      "starting to reduce usage for unit 400 with usage 1.17455 . Total units tried = 10\n",
      "try to drop unit 400 from 30 th HD.  usage down to 1.0774167115570306\n",
      "all done trying to reduce usage of unit 400 final usage = 1.02961 8847 sec elapsed 45 2 successful, failed patches, couldn't start= 0\n",
      "current avg and SD of usage are 1.00168 0.04836\n",
      "starting to reduce usage for unit 1550 with usage 1.16737 . Total units tried = 11\n",
      "try to drop unit 1550 from 33 th HD.  usage down to 1.1606510056787982\n",
      "try to drop unit 1550 from 66 th HD.  usage down to 1.1222007768693045\n",
      "try to drop unit 1550 from 99 th HD.  usage down to 1.0944555448581943\n",
      "try to drop unit 1550 from 132 th HD.  usage down to 1.0911778755922672\n",
      "try to drop unit 1550 from 165 th HD.  usage down to 1.0811373848811576\n",
      "all done trying to reduce usage of unit 1550 final usage = 1.08114 9357 sec elapsed 47 1 successful, failed patches, couldn't start= 121\n",
      "current avg and SD of usage are 1.00166 0.04754\n",
      "starting to reduce usage for unit 1641 with usage 1.14343 . Total units tried = 12\n",
      "try to drop unit 1641 from 33 th HD.  usage down to 1.0738278179211296\n",
      "all done trying to reduce usage of unit 1641 final usage = 1.02967 9393 sec elapsed 45 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00166 0.04559\n",
      "starting to reduce usage for unit 967 with usage 1.14203 . Total units tried = 13\n",
      "all done trying to reduce usage of unit 967 final usage = 1.02758 9475 sec elapsed 23 0 successful, failed patches, couldn't start= 7\n",
      "current avg and SD of usage are 1.00167 0.04418\n",
      "starting to reduce usage for unit 661 with usage 1.13956 . Total units tried = 14\n",
      "try to drop unit 661 from 48 th HD.  usage down to 1.115090281353122\n",
      "try to drop unit 661 from 96 th HD.  usage down to 1.1067236730643903\n",
      "try to drop unit 661 from 144 th HD.  usage down to 1.1028992582836152\n",
      "try to drop unit 661 from 192 th HD.  usage down to 1.0951901465242748\n",
      "try to drop unit 661 from 240 th HD.  usage down to 1.0856389229533743\n",
      "all done trying to reduce usage of unit 661 final usage = 1.08469 10625 sec elapsed 66 2 successful, failed patches, couldn't start= 176\n",
      "current avg and SD of usage are 1.00167 0.04337\n",
      "starting to reduce usage for unit 1296 with usage 1.18993 . Total units tried = 15\n",
      "try to drop unit 1296 from 14 th HD.  usage down to 1.1524568325139593\n",
      "try to drop unit 1296 from 28 th HD.  usage down to 1.1096690892866812\n",
      "try to drop unit 1296 from 42 th HD.  usage down to 1.0965233644335584\n",
      "try to drop unit 1296 from 56 th HD.  usage down to 1.0877670247265503\n",
      "try to drop unit 1296 from 70 th HD.  usage down to 1.076075082178288\n",
      "all done trying to reduce usage of unit 1296 final usage = 1.07521 10872 sec elapsed 50 8 successful, failed patches, couldn't start= 13\n",
      "current avg and SD of usage are 1.00167 0.04191\n",
      "starting to reduce usage for unit 2608 with usage 1.13516 . Total units tried = 16\n",
      "all done trying to reduce usage of unit 2608 final usage = 1.02976 10882 sec elapsed 26 0 successful, failed patches, couldn't start= 3\n",
      "current avg and SD of usage are 1.00166 0.04061\n",
      "starting to reduce usage for unit 1622 with usage 1.11246 . Total units tried = 17\n",
      "all done trying to reduce usage of unit 1622 final usage = 1.02992 10932 sec elapsed 19 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 1.00165 0.04007\n",
      "starting to reduce usage for unit 1277 with usage 1.16458 . Total units tried = 18\n",
      "try to drop unit 1277 from 15 th HD.  usage down to 1.1197474316103642\n",
      "try to drop unit 1277 from 30 th HD.  usage down to 1.0667089109354972\n",
      "try to drop unit 1277 from 45 th HD.  usage down to 1.031734020924223\n",
      "all done trying to reduce usage of unit 1277 final usage = 1.02611 11299 sec elapsed 36 6 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 1.00165 0.03865\n"
     ]
    }
   ],
   "source": [
    "#SECOND PATCHING BLOCK -- OVERUSERS.  applies a suppression of LONG STRINGS.  run first and third for MA\n",
    "maxSD = 0.04 #0.06  #0.08\n",
    "stopMaxUse = 1.+  2.* maxSD  #0.5*maxSD  #don't be too aggressive; may create long chains\n",
    "print(\"default use threshold for moving on to next overused unit is\",r5(stopMaxUse) )\n",
    "stopMaxUse = float(input(\"enter updated stopMaxUse value\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage above\",stopMaxUse)\n",
    "nBigUsers = 5\n",
    "maxExchangePop = 0.05*aDP\n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP \n",
    "print(\"this block reduces overuse, with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > stopMaxUse:\n",
    "        maxNtries +=1\n",
    "#maxNtries = int(currSD * nUnits / nDistricts)   #try up to about 10% of the districts a unit is drawn into\n",
    "#maxNtries = 10 #overrirde\n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "attemptedBigUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to reduce up to\",maxNtries,\"units' overusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedBigUs) < maxNtries: \n",
    "    #each round, find the (5) most overused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nBigFound, bigUsers = 0,0,list()\n",
    "    while nBigFound < nBigUsers:\n",
    "        consideredBigU = idx[-idxNo-1]\n",
    "        if consideredBigU not in attemptedBigUs:\n",
    "            bigUsers.append(consideredBigU)\n",
    "            nBigFound +=1\n",
    "        idxNo +=1\n",
    "    OUUclusters = [ [b] + unitNbrs[b] for b in bigUsers ]\n",
    "    bigOverUse = [np.sum([(unitUse[j] - 1.) for j in OUUclusters[i] ]) for i in range(nBigUsers) ]\n",
    "    bigI = bigOverUse.index(np.max(bigOverUse))\n",
    "    OUU = bigUsers[ bigI ]  #pick the unit that centers cluster with most overuse\n",
    "    attemptedBigUs.append(OUU)  #so we don't try this unit again in a future loop\n",
    "    OUUc = OUUclusters[bigI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    print(\"starting to reduce usage for unit\",OUU,\"with usage\",r5(unitUse[OUU]),\". Total units tried =\",len(attemptedBigUs) )\n",
    "    for u in OUUc.copy():\n",
    "        if unitUse[u] < 1.:\n",
    "            OUUc.remove(u)  #...drop any underused neighbors of the primary OUU from the target sheddable cluster\n",
    "    OUU2nbrSet = set( unitNbrs[OUU])\n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.union(set(unitNbrs[u])) \n",
    "    for u in OUUc:\n",
    "        OUU2nbrSet = OUU2nbrSet.difference({u})\n",
    "    ouuHDs, ouuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if OUU in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(OUU2nbrSet) ) > 0: #the OUU or one of its overused 1-neighbors adjoins the complement\n",
    "                ouuHDs.append(t)  #so we can shed the OOUc to the complement\n",
    "                ouuDists.append( unitCP[OUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo, idx0 = 0, 0, 0, 0, np.argsort(ouuDists)\n",
    "    while unitUse[OUU] > stopMaxUse and idxNo > -0.5*len(ouuHDs): #arbitrarily only examine 50% of HDs, biasing farthest ones\n",
    "        idxNo -=1\n",
    "        if idxNo % int(0.1*len(ouuHDs)) == 0:\n",
    "            print(\"try to drop unit\",OUU,\"from\",abs(idxNo),\"th HD.  usage down to\",unitUse[OUU] )\n",
    "        t = ouuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).difference(set(OUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        if not (contig and complementContig):  #dropping the cluster creates a problem (likely an HD discontig).  Try something simpler ...\n",
    "            if len(set(unitNbrs[OUU]).intersection(HDadjoinSet) )  > 0:  #Yay! The OUU itself on border.  Try dropping just it, not the full cluster\n",
    "                HDouuSet = {OUU}\n",
    "                trySet = set(HDunitList[t]).difference( {OUU} )\n",
    "                contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        else:\n",
    "            HDouuSet = set(HDunitList[t]).intersection(set(OUUc))\n",
    "        if contig and complementContig:  #we can at least drop the cluster, let's go for more\n",
    "            #HDouuSet = set(HDunitList[t]).intersection(set(OUUc))  #the subset of the OUU cluster that's in this HD.  Defined above\n",
    "            HDouuCpop = np.sum([unitPop[u] for u in HDouuSet])\n",
    "            giveUpOnShedding = False            \n",
    "            shedCandidates, shedScores = list(), list()\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if HDouuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward far, overused\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            while HDouuCpop < maxExchangePop and not giveUpOnShedding:\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDouuCpop += unitPop[shedU]\n",
    "                        #print(\"shedding unit\",shedU,\"from HD\",t,\"total shed Pop now\", HDouuCpop)\n",
    "                        HDouuSet.add(shedU)\n",
    "                        trySet.remove(shedU)\n",
    "                        del shedScores[shedCandidates.index(shedU)]\n",
    "                        del shedCandidates[shedCandidates.index(shedU)]\n",
    "                        newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                        for u in newSheddables:\n",
    "                            if HDouuCpop + unitPop[u] <= maxExchangePop and u not in shedCandidates:\n",
    "                                shedCandidates.append(u)\n",
    "                                shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            shedSet = HDouuSet.copy()  #set(OUUc).intersection(set(HDunitList[t]))\n",
    "            trySet = set(HDunitList[t]).difference(shedSet) \n",
    "            gap = aDP - np.sum([unitPop[u] for u in trySet])\n",
    "            nearHDlist, nearHDscore = list(), list()  #these will be dynamic lists of the nearby underused units\n",
    "            for u in trySet:\n",
    "                for uu in unitNbrs[u]:\n",
    "                    if uu not in HDunitList[t] and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:\n",
    "                        nearHDlist.append(uu)\n",
    "                        nearHDscore.append(5.*(unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                        #bias toward UNDERUSED, close\n",
    "            addedSet = set( )    \n",
    "            stillGoing = True \n",
    "            while gap > maxGap and len(nearHDlist) > 0 and stillGoing:   #add the lowest-scoring neighboring underused unit until we've roughly squared the HDpop\n",
    "                nearHDscore2 = nearHDscore.copy()\n",
    "                for ij, uu in enumerate(nearHDlist):\n",
    "                    nHDnbrs = len( set(unitNbrs[uu]).intersection(trySet) )\n",
    "                    if nHDnbrs == 1 :  #BIAS AGAINST CREATING A SLIM CHAIN\n",
    "                        nearHDscore2[ij] *= 0.5   #make this score closer to zero (less negative)  #NEW FOR GA 3/11/24\n",
    "                idx, ij, notYetPicked = np.argsort(nearHDscore2), 0, True   #originally, used nearHDscore itself here\n",
    "                while ij < len(nearHDscore) and notYetPicked:        \n",
    "                    listNo = idx[ij]   #nearHDscore.index(np.min(nearHDscore))\n",
    "                    unitNoToAdd = nearHDlist[listNo]  #add this unit ...                            \n",
    "                    canAdd  = wontEnclave(unitNoToAdd, list(trySet), unitNbrs, borderUnits)\n",
    "                    if canAdd:\n",
    "                        notYetPicked = False\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    stillGoing = False  #can't add any more units; we can't without creating an enclave\n",
    "                else:\n",
    "                    gap -= unitPop[unitNoToAdd]\n",
    "                    addedSet.add(unitNoToAdd)\n",
    "                    trySet.add( unitNoToAdd)\n",
    "                    for uu in unitNbrs[unitNoToAdd]:             # ... and add its nonHD neighbors to future candidates\n",
    "                        if uu not in trySet and uu not in nearHDlist and unitPop[uu] < gap + maxGap and unitUse[uu] < 1.01:  \n",
    "                            nearHDlist.append(uu)\n",
    "                            nearHDscore.append(5.* (unitUse[uu]-1.) + unitCP[uu].distance(hdCP[t]) / avgDist[t] ) \n",
    "                            #bias toward UNDERUSED, ~close\n",
    "                    del nearHDscore[nearHDlist.index(unitNoToAdd)]        \n",
    "                    del nearHDlist[ nearHDlist.index(unitNoToAdd) ]\n",
    "                    for ijj, uu in enumerate(nearHDlist.copy()):\n",
    "                        if unitPop[uu] > gap + maxGap:   #with the added pop from another unit, this unit is now too big to add\n",
    "                            del nearHDscore[nearHDlist.index(uu)]\n",
    "                            del nearHDlist[ nearHDlist.index(uu)]\n",
    "            currPop = np.sum([unitPop[u] for u in trySet])\n",
    "            if abs(currPop - aDP) <= 2.* maxGap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addedSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t]    = currPop\n",
    "                nPatchSuccess +=1\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "        else:\n",
    "            nCouldntStart +=1\n",
    "            #print(\"Due to discontiguity, can't drop OUU cluster for HD, OUU\", t, OUU)\n",
    "    print(\"all done trying to reduce usage of unit\",OUU,\"final usage =\",r5(unitUse[OUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )\n",
    "            \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "id": "90492bd1-3320-4712-a1be-0fc321c682bd",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Here, we exchange in under-used, THEN shed over-used\n",
      "Currently, we will stop patching when the overall sd of usage is less than 0.05\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated maxSD value 0.03\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "we will stop patching on individual underused units when their usage exceeds 0.97\n",
      "this would currently cover a total of 228 units\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter updated number of units to try boosting usage 150\n",
      "enter updated stopMinUse value for ending usage boost on a unit 0.97\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "there are currently 228 units out of 1650 with usage below 0.97\n",
      "maxExchangePop is currently 0.05 fraction of avgDistrictPop\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "Enter updated maxExchangePop fraction 0.03\n",
      "enter 1 to print out stats for every patched HD, otherwise enter reporting frequency 10\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Let's further tighten the distro with exchanges up to 23164\n",
      "current avg and SD of unit usage are 0.99949 0.04454 . Now trying to increase up to 150 units' underusage\n",
      "all done trying to reduce usage of unit 699 final usage = 0.97145 5 sec elapsed 35 32 successful, failed patches, couldn't start= 10\n",
      "current avg and SD of usage are 0.9995 0.04374\n",
      "all done trying to reduce usage of unit 775 final usage = 0.84636 7 sec elapsed 2 21 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 0.9995 0.04363\n",
      "all done trying to reduce usage of unit 778 final usage = 0.93854 14 sec elapsed 27 19 successful, failed patches, couldn't start= 24\n",
      "current avg and SD of usage are 0.99951 0.04306\n",
      "all done trying to reduce usage of unit 726 final usage = 0.89843 22 sec elapsed 28 100 successful, failed patches, couldn't start= 29\n",
      "current avg and SD of usage are 0.99952 0.04238\n",
      "all done trying to reduce usage of unit 727 final usage = 0.9712 30 sec elapsed 38 39 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 0.99953 0.0417\n",
      "all done trying to reduce usage of unit 1611 final usage = 0.97236 36 sec elapsed 23 0 successful, failed patches, couldn't start= 5\n",
      "current avg and SD of usage are 0.99953 0.04131\n",
      "all done trying to reduce usage of unit 618 final usage = 0.8655 38 sec elapsed 5 18 successful, failed patches, couldn't start= 19\n",
      "current avg and SD of usage are 0.99954 0.04108\n",
      "all done trying to reduce usage of unit 617 final usage = 0.88308 41 sec elapsed 9 6 successful, failed patches, couldn't start= 14\n",
      "current avg and SD of usage are 0.99953 0.04079\n",
      "all done trying to reduce usage of unit 866 final usage = 0.88738 46 sec elapsed 9 11 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99954 0.04057\n",
      "starting to increase usage for unit 1606 with usage 0.86625 . Total UU units tried = 10\n",
      "all done trying to reduce usage of unit 1606 final usage = 0.97485 50 sec elapsed 26 0 successful, failed patches, couldn't start= 1\n",
      "current avg and SD of usage are 0.99955 0.03991\n",
      "all done trying to reduce usage of unit 1279 final usage = 0.97492 56 sec elapsed 30 1 successful, failed patches, couldn't start= 23\n",
      "current avg and SD of usage are 0.99958 0.03911\n",
      "all done trying to reduce usage of unit 745 final usage = 0.97346 62 sec elapsed 26 27 successful, failed patches, couldn't start= 15\n",
      "current avg and SD of usage are 0.99958 0.03859\n",
      "all done trying to reduce usage of unit 1638 final usage = 0.97341 66 sec elapsed 17 0 successful, failed patches, couldn't start= 6\n",
      "current avg and SD of usage are 0.99959 0.0383\n",
      "all done trying to reduce usage of unit 1636 final usage = 0.97484 72 sec elapsed 18 0 successful, failed patches, couldn't start= 4\n",
      "current avg and SD of usage are 0.99959 0.03815\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "Cell \u001b[1;32mIn[178], line 147\u001b[0m\n\u001b[0;32m    145\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m excess \u001b[38;5;241m-\u001b[39m unitPop[u] \u001b[38;5;241m>\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m*\u001b[39mmaxGap \u001b[38;5;129;01mand\u001b[39;00m u \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m shedCandidates:\n\u001b[0;32m    146\u001b[0m         shedCandidates\u001b[38;5;241m.\u001b[39mappend(u)  \u001b[38;5;66;03m#we'll check enclavity if ever picked\u001b[39;00m\n\u001b[1;32m--> 147\u001b[0m         shedScores\u001b[38;5;241m.\u001b[39mappend((unitUse[u] \u001b[38;5;241m-\u001b[39m \u001b[38;5;241m1.\u001b[39m) \u001b[38;5;241m*\u001b[39m unitCP[u]\u001b[38;5;241m.\u001b[39mdistance(hdCP[t])\u001b[38;5;241m/\u001b[39mavgDist[t])\n\u001b[0;32m    148\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m kkk, u \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(shedCandidates): \u001b[38;5;66;03m#checking if this shed eliminates high-pop future sheds ...\u001b[39;00m\n\u001b[0;32m    149\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m excess \u001b[38;5;241m-\u001b[39m unitPop[u] \u001b[38;5;241m<\u001b[39m \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m\u001b[38;5;241m*\u001b[39mmaxGap:\n",
      "File \u001b[1;32m~\\AppData\\Local\\anaconda3\\Lib\\site-packages\\shapely\\geometry\\base.py:334\u001b[0m, in \u001b[0;36mBaseGeometry.distance\u001b[1;34m(self, other)\u001b[0m\n\u001b[0;32m    332\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdistance\u001b[39m(\u001b[38;5;28mself\u001b[39m, other):\n\u001b[0;32m    333\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Unitless distance to other geometry (float)\"\"\"\u001b[39;00m\n\u001b[1;32m--> 334\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m _maybe_unpack(shapely\u001b[38;5;241m.\u001b[39mdistance(\u001b[38;5;28mself\u001b[39m, other))\n",
      "File \u001b[1;32m~\\AppData\\Local\\anaconda3\\Lib\\site-packages\\shapely\\decorators.py:77\u001b[0m, in \u001b[0;36mmultithreading_enabled.<locals>.wrapped\u001b[1;34m(*args, **kwargs)\u001b[0m\n\u001b[0;32m     75\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m arr \u001b[38;5;129;01min\u001b[39;00m array_args:\n\u001b[0;32m     76\u001b[0m         arr\u001b[38;5;241m.\u001b[39mflags\u001b[38;5;241m.\u001b[39mwriteable \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m---> 77\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m func(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[0;32m     78\u001b[0m \u001b[38;5;28;01mfinally\u001b[39;00m:\n\u001b[0;32m     79\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m arr, old_flag \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mzip\u001b[39m(array_args, old_flags):\n",
      "File \u001b[1;32m~\\AppData\\Local\\anaconda3\\Lib\\site-packages\\shapely\\measurement.py:72\u001b[0m, in \u001b[0;36mdistance\u001b[1;34m(a, b, **kwargs)\u001b[0m\n\u001b[0;32m     47\u001b[0m \u001b[38;5;129m@multithreading_enabled\u001b[39m\n\u001b[0;32m     48\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdistance\u001b[39m(a, b, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m     49\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Computes the Cartesian distance between two geometries.\u001b[39;00m\n\u001b[0;32m     50\u001b[0m \n\u001b[0;32m     51\u001b[0m \u001b[38;5;124;03m    Parameters\u001b[39;00m\n\u001b[1;32m   (...)\u001b[0m\n\u001b[0;32m     70\u001b[0m \u001b[38;5;124;03m    nan\u001b[39;00m\n\u001b[0;32m     71\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[1;32m---> 72\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m lib\u001b[38;5;241m.\u001b[39mdistance(a, b, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "#OPTIONAL ADDITIONAL ROUND OF UNDERPOPPED.  USED FOR MD, NOT NEEDED FOR MI or MN\n",
    "print(\"Here, we exchange in under-used, THEN shed over-used\")\n",
    "maxSD = 0.05  #0.07  #0.05   #adjust down if distro already tight\n",
    "print(\"Currently, we will stop patching when the overall sd of usage is less than\",maxSD)\n",
    "maxSD = float(input(\"enter updated maxSD value\"))\n",
    "stopMinUse = 1. - maxSD\n",
    "print(\"we will stop patching on individual underused units when their usage exceeds\",r5(stopMinUse))\n",
    "maxNtries = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        maxNtries +=1\n",
    "print(\"this would currently cover a total of\",maxNtries,\"units\")\n",
    "maxNtries = int(input(\"enter updated number of units to try boosting usage\"))\n",
    "stopMinUse = float(input(\"enter updated stopMinUse value for ending usage boost on a unit\"))\n",
    "nInPlay = 0\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < stopMinUse:\n",
    "        nInPlay +=1\n",
    "print(\"there are currently\",nInPlay,\"units out of\",nUnits,\"with usage below\",stopMinUse)\n",
    "nSmallUsers = 5\n",
    "maxExchangePop = 0.05*aDP \n",
    "print(\"maxExchangePop is currently\",r5(maxExchangePop/aDP),\"fraction of avgDistrictPop\")\n",
    "newMEPratio = float(input(\"Enter updated maxExchangePop fraction\"))\n",
    "maxExchangePop = newMEPratio*aDP\n",
    "debug1 = int(input(\"enter 1 to print out stats for every patched HD, otherwise enter reporting frequency\"))\n",
    "print(\"Let's further tighten the distro with exchanges up to\",int(maxExchangePop)) #1/25/24\n",
    "maxGap = 0.9 * np.median(unitPop) \n",
    "currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "\n",
    "attemptedSmallUs = list()\n",
    "print(\"current avg and SD of unit usage are\",r5(currAvg), r5(currSD),\". Now trying to increase up to\",maxNtries,\"units' underusage\" )\n",
    "startTime = time.time()\n",
    "while currSD > maxSD and len(attemptedSmallUs) < maxNtries: \n",
    "    #each round, find the (5) most underused not-yet-tried units. Pick the unit w/ most overuse of it + 1-nbrs\n",
    "    idx = np.argsort(unitUse)\n",
    "    idxNo, nSmallFound, smallUsers = 0,0,list()\n",
    "    while nSmallFound < nSmallUsers:\n",
    "        consideredSmallU = idx[idxNo]\n",
    "        if consideredSmallU not in attemptedSmallUs:\n",
    "            smallUsers.append(consideredSmallU)\n",
    "            nSmallFound +=1\n",
    "        idxNo +=1\n",
    "    UUUclusters = [ [b] + unitNbrs[b] for b in smallUsers ]\n",
    "    smallUnderUse = [np.sum([(unitUse[j] - 1.) for j in UUUclusters[i] ]) for i in range(nSmallUsers) ]\n",
    "    smallI = smallUnderUse.index(np.max(smallUnderUse))\n",
    "    UUU = smallUsers[ smallI ]  #pick the unit that centers cluster with least composite use\n",
    "    attemptedSmallUs.append(UUU)  #so we don't try this unit again in a future loop\n",
    "    UUUc = UUUclusters[smallI]  #the list of this unit and ALL its neighbors (to be curated below ...)\n",
    "    if len(attemptedSmallUs) % debug1 == 0:\n",
    "        print(\"starting to increase usage for unit\",UUU,\"with usage\",r5(unitUse[UUU]),\". Total UU units tried =\",len(attemptedSmallUs) )\n",
    "    for u in UUUc.copy():\n",
    "        if unitUse[u] > 1.:\n",
    "            UUUc.remove(u)  #...drop any overused neighbors of the primary UUU from the target sheddable cluster\n",
    "    uuuHDs, uuuDists = list(), list()\n",
    "    for t in popHDlist:  #finding all HDs with at least one cluster member on the boundary\n",
    "        if UUU not in HDunitList[t]:\n",
    "            HDadjoinSet = set( getAdjoiners(HDunitList[t],unitNbrs) )\n",
    "            if len(HDadjoinSet.intersection(UUUc) ) > 0: #the UUU or one of its underused 1-neighbors adjoins this HD\n",
    "                uuuHDs.append(t)  #Note: we'll check later if we can contiguously pick up the UUU's cluster\n",
    "                uuuDists.append( unitCP[UUU].distance(hdCP[t]) / avgDist[t] )\n",
    "    idx0 = np.argsort(uuuDists)\n",
    "    nPatchSuccess, nPatchFail, nCouldntStart, idxNo = 0,0,0,-1\n",
    "    while unitUse[UUU] < stopMinUse and idxNo < 0.8*len(uuuHDs): #arbitrarily only examine 80% closest of HDs\n",
    "        excess, giveUpOnShedding = 99*aDP, True  #default = failed swap\n",
    "        idxNo += 1\n",
    "        if idxNo % 20 == 0 and debug1 == 1:\n",
    "            print(\"try to add unit\",UUU,\"from\",abs(idxNo),\"th HD.  Usage up to\",unitUse[UUU] )\n",
    "        t = uuuHDs[idx0[idxNo]]\n",
    "        trySet = set(HDunitList[t]).union(set(UUUc))\n",
    "        contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "        loopUUUc = UUUc.copy()  #default; we will add whole cluster\n",
    "        if not (contig and complementContig): #we can't add whole cluster; neighbors may be enclavy.   Try just adding the UUU\n",
    "            trySet = set(HDunitList[t]).union({UUU})\n",
    "            contig,complementContig, __, ___ = enclaveCheck(list(trySet), unitNbrs)\n",
    "            loopUUUc = [UUU]\n",
    "        if contig and complementContig:  #we can at least add the cluster, let's go for more\n",
    "            HDuuuSet = set(loopUUUc).difference(set(HDunitList[t]))  #the subset of the UUU cluster that adjoins (NOT in) this HD\n",
    "            HDuuuCpop = np.sum([unitPop[u] for u in HDuuuSet])\n",
    "            giveUpOnAdding = False            \n",
    "            addCandidates, addUseDists = list(), list()\n",
    "            uuCandidates = getAdjoiners(trySet, unitNbrs)  #any adjoiner can be picked up, even if far from UUUc\n",
    "            for u in uuCandidates:\n",
    "                if HDuuuCpop + unitPop[u] <= maxExchangePop:\n",
    "                    addCandidates.append(u)  #Below's relative scoring of use and distance is a bit arbitrary\n",
    "                    addUseDists.append((unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t])  #bias toward close, underused\n",
    "            if len(addCandidates) == 0:\n",
    "                giveUpOnAdding = True\n",
    "            while HDuuuCpop < maxExchangePop and not giveUpOnAdding:\n",
    "                addNneighbors = [len( set(unitNbrs[addC]).intersection(trySet) ) for addC in addCandidates ]\n",
    "                addScores = addUseDists.copy()\n",
    "                for jjj, u in enumerate(addCandidates):\n",
    "                    if addNneighbors[jjj] == 1:\n",
    "                        addScores[jjj] += 0.4321    #discourage growing fingers\n",
    "                #print(\"HDuuuCpop is now\",HDuuuCpop)\n",
    "                idx, ij, notYetPicked = np.argsort(addScores), 0, True\n",
    "                while ij < 0.5*len(addScores) and notYetPicked:\n",
    "                    listNo = idx[ij]   #work from low to high score\n",
    "                    addU = addCandidates[listNo]\n",
    "                    contig,cContig, __, ___ = enclaveCheck(list(trySet.union({addU}) ), unitNbrs)\n",
    "                    if contig and cContig:\n",
    "                        notYetPicked = False\n",
    "                        HDuuuCpop += unitPop[addU]\n",
    "                        HDuuuSet.add(addU)\n",
    "                        trySet.add(addU)\n",
    "                        del addUseDists[addCandidates.index(addU)]\n",
    "                        del addCandidates[addCandidates.index(addU)]                        \n",
    "                        for uu in list(set(unitNbrs[addU]).difference(trySet) ): \n",
    "                            if uu not in addCandidates and unitPop[uu] + HDuuuCpop < maxExchangePop and unitUse[uu] < 1.01:\n",
    "                                addCandidates.append(uu)\n",
    "                                addUseDists.append( (unitUse[uu]-1.) + 0.1*unitCP[uu].distance(hdCP[t]) / avgDist[t] )\n",
    "                    else:\n",
    "                        ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnAdding = True  #all candidates would create a discontig, so can't shed any more units\n",
    "            addSet = HDuuuSet.copy()  #we're done building the list of underused units to add to this HD\n",
    "            trySet = set(HDunitList[t]).union(addSet) \n",
    "            excess = np.sum([unitPop[u] for u in trySet]) - aDP\n",
    "            shedCandidates, shedScores, giveUpOnShedding = list(), list(), False\n",
    "            bdryCandidates = getBdryNonEdgers(trySet, unitNbrs)  #new - any boundary unit can be shed, even if far from OUUc\n",
    "            for u in bdryCandidates:\n",
    "                if unitPop[u] <= excess + maxGap:\n",
    "                    shedCandidates.append(u)\n",
    "                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])  #bias toward OVERUSED, far\n",
    "            if len(shedCandidates) == 0:\n",
    "                giveUpOnShedding = True\n",
    "            shedSet = set()\n",
    "            while excess > maxGap and not giveUpOnShedding:\n",
    "                #print(\"excess pop is now\",excess,\"for HD\",t)\n",
    "                idx, ij, notYetPicked = np.argsort(shedScores), 0, True\n",
    "                while ij < len(shedScores) and notYetPicked:\n",
    "                    listNo = idx[-1-ij]   #work from high to low score\n",
    "                    shedU = shedCandidates[listNo]\n",
    "                    if shedScores[listNo] <= 0:  #we're delving into the underused; stop adding to shed list\n",
    "                        break\n",
    "                    if excess - unitPop[shedU] >= -1*maxGap:\n",
    "                        contig,cContig, __, ___ = enclaveCheck(list(trySet.difference({shedU}) ), unitNbrs)\n",
    "                        if contig and cContig:\n",
    "                            notYetPicked = False\n",
    "                            excess -= unitPop[shedU]\n",
    "                            trySet.remove(shedU)\n",
    "                            shedSet.add(shedU)\n",
    "                            del shedScores[shedCandidates.index(shedU)]\n",
    "                            del shedCandidates[shedCandidates.index(shedU)]\n",
    "                            newSheddables = set(unitNbrs[shedU]).intersection(trySet)\n",
    "                            for u in newSheddables:\n",
    "                                if excess - unitPop[u] >= -1*maxGap and u not in shedCandidates:\n",
    "                                    shedCandidates.append(u)  #we'll check enclavity if ever picked\n",
    "                                    shedScores.append((unitUse[u] - 1.) * unitCP[u].distance(hdCP[t])/avgDist[t])\n",
    "                            for kkk, u in enumerate(shedCandidates): #checking if this shed eliminates high-pop future sheds ...\n",
    "                                if excess - unitPop[u] < -1*maxGap:\n",
    "                                    del shedScores[kkk]\n",
    "                                    del shedCandidates[kkk]\n",
    "                    ij +=1\n",
    "                if notYetPicked:\n",
    "                    giveUpOnShedding = True  #all shedcandidates would create a discontig, so can't shed enough units to square pop\n",
    "            legitSwap = False\n",
    "            if abs(excess) <= 2.*maxGap:  #giving ourselves a bit more margin after exchanges\n",
    "                contig,cContig, __, ___ = enclaveCheck(list(trySet), unitNbrs) \n",
    "                if contig and cContig:\n",
    "                    legitSwap = True\n",
    "            if legitSwap:\n",
    "                for u in shedSet:\n",
    "                    unitUse[u] -= HDweight[t] * nDistricts\n",
    "                for u in addSet:\n",
    "                    unitUse[u] += HDweight[t] * nDistricts\n",
    "                HDunitList[t] = list(trySet)\n",
    "                HDvPop[t] = np.sum([ unitPop[u] for u in HDunitList[t] ])\n",
    "                nPatchSuccess +=1\n",
    "                #print(\"we added\",addSet,\"and shed units\",shedSet,\"from HD\",t)\n",
    "            else:\n",
    "                nPatchFail +=1\n",
    "        else:  #adding neither the UUU cluster or just the UUU worked; couldn't even start\n",
    "            nCouldntStart +=1\n",
    "            # end of shed + add patching on this HD\n",
    "            #print(\"shed and patched for HD, OUU\",t,OUU)\n",
    "\n",
    "    print(\"all done trying to reduce usage of unit\",UUU,\"final usage =\",r5(unitUse[UUU]),int(time.time()-startTime),\"sec elapsed\",\n",
    "         nPatchSuccess,nPatchFail,\"successful, failed patches, couldn't start=\",nCouldntStart)\n",
    "    currAvg, currSD = getWeightedAvgAndSD(unitUse,unitPop)\n",
    "    print(\"current avg and SD of usage are\",r5(currAvg), r5(currSD) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "cb60da52-ca13-45dd-8bf0-475213183a0d",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "overused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "underused units\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"overused units\")\n",
    "maxPlot = 1.06\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] > maxPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()\n",
    "print(\"underused units\")\n",
    "minPlot = 0.94\n",
    "for u in range(nUnits):\n",
    "    if unitUse[u] < minPlot:\n",
    "        plotPoly(unitGeom[u])\n",
    "        plotCenter(round(unitUse[u],2),unitGeom[u])\n",
    "plotPoly(MAP,0.2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa912158-e8e9-46f3-8c3d-f6b17c26e62c",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Note - for MA, above is second run-through after overuse, then underuse pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "0d4f1372-6044-4803-91d9-de4b95a40083",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "unpatched, patched use avgs are 1.00204 1.00165 and their SDs are 0.10232 0.03865\n",
      "And here is the pop distro\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "checking contiguity of final HDs\n",
      "working on HD 0 out of 4110\n",
      "working on HD 300 out of 4110\n",
      "working on HD 600 out of 4110\n",
      "working on HD 900 out of 4110\n",
      "working on HD 1200 out of 4110\n",
      "working on HD 1500 out of 4110\n",
      "working on HD 1800 out of 4110\n",
      "working on HD 2100 out of 4110\n",
      "working on HD 2400 out of 4110\n",
      "working on HD 2700 out of 4110\n",
      "working on HD 3000 out of 4110\n",
      "working on HD 3300 out of 4110\n",
      "working on HD 3600 out of 4110\n",
      "working on HD 3900 out of 4110\n",
      "all done checking HD and complement contiguity for all 4110 HDs\n"
     ]
    }
   ],
   "source": [
    "patchedUse, unpUse = [0.]*nUnits, [0.]*nUnits\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        patchedUse[u] += HDweight[t] * nDistricts\n",
    "    for u in unpatchedHDlist[t]:\n",
    "        unpUse[u] += HDweight[t] * nDistricts\n",
    "plt.hist(patchedUse,bins=50, label=\"patched\",histtype=\"step\")\n",
    "plt.hist(unpUse, bins=50, label=\"unpatched\",histtype=\"step\")\n",
    "plt.legend()\n",
    "plt.show()\n",
    "patchedAvg, patchedSD = getWeightedAvgAndSD(patchedUse,unitPop)\n",
    "unpatchedAvg, unpatchedSD = getWeightedAvgAndSD(unpUse,unitPop)\n",
    "print(\"unpatched, patched use avgs are\",r5(unpatchedAvg), r5(patchedAvg),\"and their SDs are\",r5(unpatchedSD), r5(patchedSD) )\n",
    "print(\"And here is the pop distro\")\n",
    "plt.hist([HDvPop[t] for t in popHDlist])\n",
    "plt.axvline(aDP, ls=\"--\",color=\"orange\")\n",
    "plt.show()\n",
    "print(\"checking contiguity of final HDs\")\n",
    "for t in popHDlist:\n",
    "    if t%300 == 0:\n",
    "        print(\"working on HD\",t,\"out of\",nHDs)\n",
    "    unbroken, noEnclave, sList, eList = enclaveCheck(HDunitList[t], unitNbrs)  #these HDunitLists now appear to be sets\n",
    "    if not unbroken or not noEnclave:\n",
    "        print(\"uh-oh, HD\",t,\"has contiguity, complement-contiguity of\",unbroken, noEnclave)\n",
    "print(\"all done checking HD and complement contiguity for all\",nHDs,\"HDs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "ac9cd133-94f0-494b-ac74-0c584482d97e",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Lets write these UNIT lists to a file\n"
     ]
    }
   ],
   "source": [
    "print(\"Lets write these UNIT lists to a file\")\n",
    "HDvPop = [0. for t in range(nHDs)]  #writing UNIT lists to a file\n",
    "tList = [t for t in range(nHDs)]\n",
    "for t in popHDlist:\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDunitList\":HDunitList,\n",
    "                      \"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"fullyPatched.csv\" #\"contigUnpatchedB.csv\"\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "id": "26b87c95-101f-4f8f-bb73-feb1827ac6b5",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    }
   ],
   "source": [
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))\n",
    "if noFrag == 1:\n",
    "    nFragmentedVTDs,fragmentedVTDs = 0, list()\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "ec102553-e4f3-4010-86bc-725a01b95788",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter([v for v in range(len(parentVTDno))],parentVTDno)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 270,
   "id": "55d64c64-b473-49d0-b863-d4123cbb9b6c",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": [
    "for v in range(nVTDs):\n",
    "    if MAP.contains(vtdGeom[v].centroid) and v not in parentVTDno:\n",
    "        print(v,\"is in the map but not in the parent vtd list\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "ecd50c96-51ce-4d83-b0df-e8c645c35815",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after above patching, write these contiguous lists to a file, converting to vtd lists\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter 1 if there were NO fragmented VTDs 0\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "working on full or partial VTD master list for unit 0\n",
      "working on full or partial VTD master list for unit 2000\n",
      "Now converting unit lists to vtd lists for all HDs\n"
     ]
    }
   ],
   "source": [
    "#THIS WORKS FOR BOTH VTD- AND UNIT-BASED (FRAG VTD) -- **NOTE: DOES NOT ADD IN CUT DISTRICTS AND REBALANCE WEIGHTS\n",
    "print(\"after above patching, write these contiguous lists to a file, converting to vtd lists\")\n",
    "noFrag = int(input(\"enter 1 if there were NO fragmented VTDs\"))  #for simple states where units are at least whole vtd's\n",
    "tList = [t for t in range(nHDs)]\n",
    "vtdList = [list() for t in range(nHDs)]\n",
    "unitVTDlist, unitFragVTDlist, unitVTDfrac = [list() for u in range(nUnits)], [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "unitFullVTDlist, unitPartialVTDlist =       [list() for u in range(nUnits)], [list() for u in range(nUnits)]\n",
    "\n",
    "for u in range(nUnits):\n",
    "    if u %2000 == 0:\n",
    "        print(\"working on full or partial VTD master list for unit\",u)\n",
    "    if allUnits[u] % 1 == 0.5 :\n",
    "        c = int(allUnits[u])\n",
    "        unitVTDlist[u] = countyTractList[c].copy()\n",
    "        unitFullVTDlist[u] = countyTractList[c].copy()\n",
    "    if allUnits[u] % 1 == 0.25 :\n",
    "        CCBnumber = int(allUnits[u])\n",
    "        for c in CCBlist[CCBnumber] :\n",
    "            unitVTDlist[u] += countyTractList[c]\n",
    "            unitFullVTDlist[u] += countyTractList[c]\n",
    "    if allUnits[u] % 1 == 0:\n",
    "        if noFrag == 1:\n",
    "            unitVTDlist[u].append(allUnits[u] )\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitVTDlist[u].append(surroundedVTDs[i])\n",
    "        else:\n",
    "            unitFragVTDlist[u].append(allUnits[u])\n",
    "            for i,vv in enumerate(surrounders):\n",
    "                if allUnits[u] == vv:\n",
    "                    unitFragVTDlist[u].append(surroundedVTDs[i])\n",
    "            vtdFrac = [0. for V in range(nVTDs)]\n",
    "            for vv in unitFragVTDlist[u]:\n",
    "                V = parentVTDno[vv]\n",
    "                if len(VTDchildren[V]) == 1:  #nonfragmented vtd\n",
    "                    vtdFrac[V] = 1.\n",
    "                else:\n",
    "                    if tractPop[V] > 0:\n",
    "                        vtdFrac[V] += fragVTDgeom[vv].area / vtdGeom[V].area #fragVTDpop[uu] / tractPop[v]  #we overwrote the frag pops earlier; can't use\n",
    "            for v in range(nVTDs):\n",
    "                if vtdFrac[v] > 0.0001:\n",
    "                    if vtdFrac[v] > 0.999:\n",
    "                        unitFullVTDlist[u].append(v)\n",
    "                    else:\n",
    "                        unitPartialVTDlist[u].append(v)\n",
    "                        unitVTDfrac[u].append(vtdFrac[v] )\n",
    "                                    \n",
    "HDpartialVTDlist, HDfullVTDlist, HDvtdFrac = [list() for t in range(nHDs)] ,[list() for t in range(nHDs)],[list() for t in range(nHDs)]               \n",
    "print(\"Now converting unit lists to vtd lists for all HDs\")\n",
    "if noFrag == 1:\n",
    "    for t in popHDlist:\n",
    "        for u in HDunitList[t]:\n",
    "            vtdList[t] += unitVTDlist[u]\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":vtdList,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "else:\n",
    "    for t in popHDlist:\n",
    "        partialList, partialFrac = list(), list()  #for many HDs, we'll recover whole VTDs when aggregating units\n",
    "        for u in HDunitList[t]:\n",
    "            HDfullVTDlist[t] +=   unitFullVTDlist[u] \n",
    "            partialList +=         unitPartialVTDlist[u]\n",
    "            partialFrac +=          unitVTDfrac[u]\n",
    "        partialSet = set(partialList)  #non-duplicated set of partials across the HD, prepping to aggregate where possible\n",
    "        partialSetFrac, partialSetList = [0. for v in partialSet], list(partialSet)\n",
    "        for i,v in enumerate(partialList):\n",
    "            partialSetFrac[partialSetList.index(v)] += partialFrac[i]\n",
    "        for i,v in enumerate(partialSetList):\n",
    "            if partialSetFrac[i] > 0.999:  #the district has all the fragments of the original VTD contained in the HD's units\n",
    "                HDfullVTDlist[t].append(v)\n",
    "            else:\n",
    "                HDpartialVTDlist[t].append(v)\n",
    "                HDvtdFrac[t].append(      r5(partialSetFrac[i]) )  #save the aggregated fraction of this VTD across all units\n",
    "    outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                           \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "id": "5075814f-4a75-4807-ad8d-b3cc969cb470",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7211 7213 7211 7211 7211 7211\n"
     ]
    }
   ],
   "source": [
    "\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDvPop = HDvPop[0:nHDs]\n",
    "HDweight = HDweight[0:nHDs]\n",
    "HDfullVTDlist = HDfullVTDlist[0:nHDs]\n",
    "HDpartialVTDlist = HDpartialVTDlist[0:nHDs]\n",
    "HDvtdFrac = HDvtdFrac[0:nHDs]\n",
    "hdCPx, hdCPy = hdCPx[0:nHDs], hdCPy[0:nHDs]\n",
    "print(nHDs,len(tList), len(HDweight), len(HDvPop), len(HDvtdFrac), len(hdCPx) )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "e385f357-5b7e-46f5-b054-c5c38d799395",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0 4110\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight), nHDs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 273,
   "id": "8d922813-2854-41d7-9405-22db5d5d5a59",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now append the cut districts and adjust the HDweights\n",
      "12 1 are the number of HD-drawn and cut districts\n"
     ]
    }
   ],
   "source": [
    "print(\"Now append the cut districts and adjust the HDweights\")\n",
    "print(nDistricts,nCutDistricts,\"are the number of HD-drawn and cut districts\")\n",
    "HDweight = [nDistricts/float(nCutDistricts + nDistricts) * HDweight[t] for t in range(nHDs)]\n",
    "tList = [t for t in range(nHDs)]\n",
    "if type(hdCPx) != type(list()):\n",
    "    hdCPx, hdCPy = hdCPx.to_list(), hdCPy.to_list()\n",
    "for L in allCutLists:\n",
    "    tList.append(len(tList))\n",
    "    HDweight.append(1./(nCutDistricts + nDistricts))\n",
    "    pop = np.sum([tractPop[v] for v in L])\n",
    "    HDvPop.append(pop )\n",
    "    HDfullVTDlist.append(L)\n",
    "    HDpartialVTDlist.append(list() )\n",
    "    HDvtdFrac.append(list() )\n",
    "    hdCPx.append(np.sum([tractPop[v]*tractCPx[v] for v in L]) / pop )\n",
    "    hdCPy.append(np.sum([tractPop[v]*tractCPy[v] for v in L]) / pop )\n",
    "    \n",
    "\n",
    "outDF = pd.DataFrame( {\"tract\":tList,\"HDweight\":HDweight,\"HDvPop\":HDvPop,\"HDvtdList\":HDfullVTDlist,\"partials\":HDpartialVTDlist,\n",
    "                        \"HDvtdFrac\":HDvtdFrac,\"centroid x\":hdCPx, \"centroid y\":hdCPy} )\n",
    "outname = STATE+str(int(nHDs))+\"patchedWithCutsVTDs.csv\"   #patchDown, PatchUp, PatchBoth\n",
    "outpath = \"2024state_HD_output/\"+outname\n",
    "outDF.to_csv(outpath)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 274,
   "id": "b0b611f7-6c35-495d-b38c-c848317d63ab",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1.0\n"
     ]
    }
   ],
   "source": [
    "print(np.sum(HDweight))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "b9d808de-119f-4197-8e0c-8407c105d789",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "vtdUSE = [0. for v in range(nVTDs)]\n",
    "for u in range(nUnits):\n",
    "    for v in unitFullVTDlist[u]:\n",
    "        vtdUSE[v] += 1\n",
    "    for i,v in enumerate(unitPartialVTDlist[u]):\n",
    "        vtdUSE[v] += unitVTDfrac[u][i]\n",
    "\n",
    "plt.scatter([v for v in range(nVTDs)], vtdUSE)\n",
    "plt.show()\n",
    "unused = list()\n",
    "for v in range(nVTDs):\n",
    "    if vtdUSE[v] < 0.2 and MAP.contains(vtdGeom[v].centroid) and tractPop[v] > 0:\n",
    "        unused.append(v)\n",
    "        #print(v,\"in county\",countyNo[v],\"has pop\",tractPop[v],\"and map-total usage of\",vtdUSE[v],\"its surroundedness is\",v in surroundedVTDs)\n",
    "        plotPoly(vtdGeom[v].centroid.buffer(0.1))\n",
    "        plotCenter(v,vtdGeom[v],8)\n",
    "    #if vtdUSE[v] > 0.2 and vtdUSE[v] < 0.95:\n",
    "    #    plotCenter(r3(vtdUSE[v]),vtdGeom[v])\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "3d2a393c-5ab8-4140-80eb-1153c2ef41f9",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for u in range(nUnits):\n",
    "    if unitUse[u]  < 0.9:\n",
    "        plotPoly(unitGeom[u],0.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "    if  unitUse[u]  > 1.1:\n",
    "        plotPoly(unitGeom[u],1.2)\n",
    "        plotCenter(r3(unitUse[u]),unitGeom[u],6)\n",
    "plotPoly(MAP)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "404935e6-f0de-4b51-9db9-020aa208f852",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "integrity check: vtd-based pops\n",
      "x = n surrounded, y= unit - vtd-based\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"integrity check: vtd-based pops\")\n",
    "HDvtdbasedPop = [0. for t in range(nHDs)]\n",
    "HDvPop = [0. for t in range(nHDs)]\n",
    "nSurrs = [0. for t in range(nHDs)]\n",
    "for t in range(nHDs):\n",
    "    for u in HDunitList[t]:\n",
    "        HDvPop[t] += unitPop[u]\n",
    "        if u in surroundedVTDs:\n",
    "            nSurrs[t] += 1\n",
    "    for v in HDfullVTDlist[t]:\n",
    "        HDvtdbasedPop[t] += origVTDpop[v] #tractPop[v]\n",
    "    for i,v in enumerate(HDpartialVTDlist[t]):\n",
    "        HDvtdbasedPop[t] += HDvtdFrac[t][i] * origVTDpop[v] #tractPop[v] also works\n",
    "        \n",
    "plt.scatter([nSurrs[t] for t in popHDlist], [HDvPop[t] - HDvtdbasedPop[t] for t in popHDlist] )\n",
    "print(\"x = n surrounded, y= unit - vtd-based\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ef27af54-daf5-4e8f-9230-bce5b0b1e705",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "3ad3342b-b8e3-46f5-a3e5-f49df386b88f",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\n",
      "Let's read in the 2020 and 2016 voting data for MN\n",
      "In year/election 2020 Dem and GOP total votes were 1717072 1484060 for a stateGOP of 0.4636\n",
      "There are a total of 4110  vote-mapped voting districts from election(s) in year  2020\n",
      "In year/election 2016 Dem and GOP total votes were 1367713 1322947 for a stateGOP of 0.49168\n",
      "There are a total of 4110  vote-mapped voting districts from election(s) in year  2016\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, read in the votes by vtd to compute ensemble vote margin vs. true state vote margin\")\n",
    "#note: we started w possibility of separate election --> 2020 vtd files by year.  Now we use ALARM combined 2016+2020 --> 2020 csv's for all exc CA\n",
    "# copied from \"HDpartisanAnalysis\"\n",
    "print(\"Let's read in the 2020 and 2016 voting data for\",STATE)\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G16PREDCLI\"], [\"G16PRERTRU\" ], list()\n",
    "#DemCandidates, RepCandidates, vestDFs = [\"G20PREDBID\", \"G16PREDCli\"], [\"G20PRERTRU\" ,\"G16PRERTru\" ], list()\n",
    "DemCandidates, RepCandidates, vestDFs = [\"pre_20_dem_bid\", \"pre_16_dem_cli\"], [\"pre_20_rep_tru\" ,\"pre_16_rep_tru\" ], list()\n",
    "nYears = 2\n",
    "unitIDs, vestReps,vestDems,yearLean = [list()]*nYears, [0]*nYears, [0]*nYears, [0.5]*nYears\n",
    "years = [str(2020),str(2016)]\n",
    "DemVotes, RepVotes = [list() for y in years], [list() for y in years]\n",
    "vestDir = \"./state_map_files/\" + STATE.lower()\n",
    "vestDF = pd.read_csv(vestDir + \"_2020_vtd.csv\")\n",
    "mergedDF = vestDF.copy() #pd.merge(mergedDF,vestDF, on = \"GEOID20\")\n",
    "for y,year in enumerate(years):\n",
    "    DemVotes[y], RepVotes[y], unitIDs[y] = mergedDF[DemCandidates[y]], mergedDF[RepCandidates[y]], vestDF[(\"GEOID20\")]\n",
    "    vestDems[y], vestReps[y] = np.sum(DemVotes[y]), np.sum(RepVotes[y])\n",
    "    yearLean[y] = vestReps[y]/float(vestDems[y]+vestReps[y])\n",
    "    print(\"In year/election\",year,\"Dem and GOP total votes were\",int(vestDems[y]),int(vestReps[y]),\"for a stateGOP of\",r5(yearLean[y]) )\n",
    "    nVTDs = len(DemVotes[y])\n",
    "    print(\"There are a total of\",nVTDs,\" vote-mapped voting districts from election(s) in year \",years[y])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f628069d-4177-401e-bf49-b7f194d0ef8b",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "5cf73783-4a48-4a3f-a2e3-c1b9ff32c859",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now let's read in our ensemble of HD districts for MN\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "enter the filename with the vtd assignments to districts; e.g. MO1654contigPatchBoth.csv MN4110opt3patchedVTDs.csv\n",
      "enter the number of HD-drawn districts in the state; e.g. 8 8\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "This ensemble or enacted map describes 4110 drawn districts.  This state has 8 districts per map\n",
      "converting vtd list strings to vtd lists by drawn district ...\n",
      "the total weight across all rows should be 1.000, actually is 1.0\n",
      "I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\n",
      "translating from HD order of precinct rows to VEST order\n"
     ]
    }
   ],
   "source": [
    "print(\"Now let's read in our ensemble of HD districts for\",STATE)\n",
    "infilename = input(\"enter the filename with the vtd assignments to districts; e.g. MO1654contigPatchBoth.csv\")\n",
    "\n",
    "HDdf = pd.read_csv(\"2024state_HD_output/\"+infilename)\n",
    "nRows = len(HDdf)\n",
    "nStateDistricts = int(input(\"enter the number of HD-drawn districts in the state; e.g. 8\"))\n",
    "print(\"This ensemble or enacted map describes\",nRows,\"drawn districts.  This state has\",nStateDistricts,\"districts per map\")\n",
    "\n",
    "HDvPop = HDdf[\"HDvPop\"].to_list()\n",
    "HDweight = HDdf['HDweight'].to_list()\n",
    "#tractPop = HDdf['tractPop'].to_list()\n",
    "#statePop = np.sum(tractPop)\n",
    "tractCPx = HDdf['centroid x'].to_list()\n",
    "tractCPy = HDdf['centroid y'].to_list()\n",
    "HDvtdListString = HDdf[\"HDvtdList\"]\n",
    "print(\"converting vtd list strings to vtd lists by drawn district ...\")\n",
    "HDvtdList = [list() for t in range(nRows) ]\n",
    "for t in range(nRows):\n",
    "    if HDvtdListString[t] != \"[]\":\n",
    "        HDvtdList[t] = ast.literal_eval(HDvtdListString[t])\n",
    "\n",
    "if \"partials\" in HDdf.columns.values: #\"splitTractNo\" #.to_list():\n",
    "    splitTractList, splitTractUseList = HDdf['partials'], HDdf['HDvtdFrac']\n",
    "    splitTractNo = [ast.literal_eval(splitTractList[t])    for t in range(nRows)]\n",
    "    splitTractUse = [ast.literal_eval(splitTractUseList[t]) for t in range(nRows)]\n",
    "else :  #incoming file didn't use any partial units, only whole ones\n",
    "    splitTractNo, splitTractUse = [[] for t in range(nRows)] , [ [] for t in range(nRows)]\n",
    "\n",
    "print(\"the total weight across all rows should be 1.000, actually is\",r5(np.sum(HDweight)) )\n",
    "print(\"I am assuming we already read in a 'tractPopFile' of Census vtd geoms & pops with a GEOID20 column\")\n",
    "censusGEOID20 = tractPopFile['GEOID20']\n",
    "miniHDdf = pd.DataFrame( {\"GEOID20\":censusGEOID20} )\n",
    "vestNo = [v for v in range(nVTDs)]\n",
    "print(\"translating from HD order of precinct rows to VEST order\")\n",
    "miniVestDF = pd.DataFrame( {\"GEOID20\":mergedDF['GEOID20'], \"vestNo\":vestNo} )\n",
    "mappingDF = pd.merge(miniHDdf,miniVestDF,on=\"GEOID20\")\n",
    "vestID = mappingDF['vestNo']  #this maps each named unit in a HDVL to the correct vestNo row with voting data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "9c38b293-7a46-4106-a972-b4868206bc2d",
   "metadata": {
    "tags": []
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "540c6d1d-7728-48bf-90f0-f124b25ac7c2",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sanity check - Rep-leaning vtds for year 2020\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(\"sanity check - Rep-leaning vtds for year\",years[0])  #for MA, do GOP-leaning\n",
    "for v in range(nVTDs):\n",
    "    plotPoly(vtdGeom[v],0.2)\n",
    "    if DemVotes[0][vestID[v]] < RepVotes[0][vestID[v]]:\n",
    "        plt.text(vtdGeom[v].centroid.x, vtdGeom[v].centroid.y, \"R\", color = \"red\",fontsize=6)\n",
    "        #plotCenter(\"d\",vtdGeom[v],6)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "56ed7e9d-1400-4848-892e-737555552d58",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\n",
      "working on drawn district no 0\n",
      "working on drawn district no 1000\n",
      "working on drawn district no 2000\n",
      "working on drawn district no 3000\n",
      "working on drawn district no 4000\n",
      "here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\n",
      "true 2020: 1717072 1484060 -233012\n",
      "ensemble : 1723997 1483921 -240076\n",
      "the true and ensemble state GOP leans are 0.4636 0.4625806242169592\n"
     ]
    }
   ],
   "source": [
    "print(\"Now, let's compute the ensemble average vote margin (GOP -  Dem total votes) for 2020 vs. true statewide result\")\n",
    "nDrawnDistricts = len(HDweight)  #now including cut districts\n",
    "nMapDistricts = nCutDistricts + nDistricts\n",
    "nEnsembleDems, nEnsembleReps = [0.]*nYears, [0.]*nYears\n",
    "y=0\n",
    "for t in range(nDrawnDistricts):\n",
    "    if t%1000 == 0:\n",
    "        print(\"working on drawn district no\",t)\n",
    "    nEnsembleDems[y] += nMapDistricts* HDweight[t] * ( np.sum([DemVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([DemVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "    nEnsembleReps[y] += nMapDistricts* HDweight[t] * ( np.sum([RepVotes[y][vestID[v]] for v in HDvtdList[t] ])\n",
    "                                               + np.sum([RepVotes[y][vestID[v]] * splitTractUse[t][i] for i,v in enumerate(splitTractNo[t]) ])  )\n",
    "\n",
    "print(\"here is the table of Dem and Rep votes, vote margin for true 2020 vs. ensemble\")\n",
    "print(\"true 2020:\",int(vestDems[y]),int(vestReps[y]),              int(vestReps[y] - vestDems[y]) )\n",
    "print(\"ensemble :\",int(nEnsembleDems[y]),int(nEnsembleReps[y]),    int(nEnsembleReps[y] - nEnsembleDems[y]) )\n",
    "print(\"the true and ensemble state GOP leans are\",r5(vestReps[y]/(vestReps[y]+vestDems[y])),\n",
    "      nEnsembleReps[y]/(nEnsembleReps[y]+nEnsembleDems[y]) )"
   ]
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   "outputs": [],
   "source": []
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